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Cross-Language Retrieval
LBSC 796/INFM 718R
Douglas W. Oard
Session 12: November 26, 2007
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Agenda
&#= 8226;Questions
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&#= 8226;Overview
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&#= 8226;Cross-Language Search
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&#= 8226;User Interaction
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User Needs Assessment
<= span class=3DBB style=3D'position:absolute;left:-4.56%'>•Who are t= he potential users?
<= span style=3D'visibility:hidden'>•
<= span class=3DBB style=3D'position:absolute;left:-4.56%'>•What goal= s do we seek to support?
<= span style=3D'visibility:hidden'>•
•What lang= uage skills must we accommodate?
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Native speakers, Global Reach projection for 2004 (as= of Sept, 2003)
Global Internet Users
Until the year 2000, more than half of all users of the Internet spoke English = as their native language.  Alth= ough the total number of English speakers on the Internet continues to increas= e, the number of Internet users that speak a first language other than Engli= sh is rising far more rapidly.  The consulting firm Global Reach estimates that more that two-thirds of all Internet users presently speak a first language other than English.
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quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
3D"Web
Native speakers, Global Reach projection for 2004 (as= of Sept, 2003)
Global Internet Users
However, English still dominates the information space.  As the inner ring illustrates, m= ore than two-thirds of all Web pages are still written in English.  The same is true in our librarie= s; English is the principal language of international publishing.  In business, English is the lang= uage of commerce.  For these reas= ons, many people around the world have a working knowledge of English as a sec= ond language.  But many others do not.  If we aspire to univer= sal access, we must build systems that help all of our citizens to access the full storehouse of the world’s information. In my talk this morning= , I will review what we presently know how to do.  I’ll then close with a few remarks about how we might employ these capabilities.
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Most Widely-Spoken Languages
Source: Ethnologue (SIL), 1999
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Tracking with PRISE
Global Trade
3D"Text=
Billions of US Dollars (1999)
Sourc= e: World Trade Organization 2000 Annual Report
This chart shows the 15 nations with at least 100 billion dollars in annual imports and exports.
Together, these nations account for 73% of the world’s exports
World trade thus defines nine major languages:
English, German, Japanese, Chinese, French, Italian, Dutch, Korean, Spanish=

There are three key drivers that decide which languages get attention.

1)Where is the money.  The G7 languages are well covere= d
2)Where are the people.  This seems to have a much smaller effect.
3)Where are the problems:  This explains the interest in Fa= rsi, Korean, etc.
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Content-Type: image/gif R0lGODlhFwDFAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAcAIgAM AJwAgAAAAAAAAALZhINpG8vvXotu0pgQtc2eCnjixyjkhaZHtkkYOEKiGaob+35e7ULkrDnZhkQU J4MTKlW7V/PU3CGfxap1FXpOOi3uRRO0Un28CvJLvi6zNJeW9w6rfdN21Hasg3JzZpt8l1Y2WCLX d/NHGMP3tsaBtqLneEhpFPS3Raf5sweXFpaYMhZ5JkjYwmSaV7pWiTGaCbnIxgo4l9R5OiukFer6 i9fR6AVzimWo1pu4a5wbVbt5hWvLp5tbOFr0SItclj20Wht4GI47biQDDQUcyda57R0NP4/N2ghQ AAA7 ------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0188.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Who needs Cross-Language Search?
&#= 8226;When users can read several languages
&= #8211;Eliminate multiple queries
&= #8211;Query in most fluent language
• <= /div>
&#= 8226;Monolingual users can also benefit
&= #8211;If translations can be provided
&= #8211;If it suffices to know that a document exists
&= #8211;If text captions are used to search for images
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The Problem Space
•R= etrospective search
–W= eb search
–S= pecialized services (medicine, law, patents)
–H= elp desks
•<= /span>Real-time filtering
–E= mail spam
–W= eb parental control
–N= ews personalization
•<= /span>Real-time interaction
–I= nstant messaging
–C= hat rooms
–T= eleconferences
Key Capabilities
&#= 8226;  Map= across languages
–F= or human understanding
–F= or automated processing
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A Little (Confusing) Vocabulary
&#= 8226;Multilingual document
&= #8211;Document containing more than one language
&#= 8226;Multilingual collection
&= #8211;Collection of documents in different languages
&#= 8226;Multilingual system
&= #8211;Can retrieve from a multilingual collection
&#= 8226;Cross-language system
&= #8211;Query in one language finds document in another
&#= 8226;Translingual system
&= #8211;Queries can find documents in any language
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The Information Retrieval Cycle
Source
Selection
Search=
Query
Selection
Ranked List
Examination
Documents
Delivery
Documents
Query
Formulation
Resource
source reselection=
System discovery
Vocabulary discovery
Concept discovery
Document discovery
How do you formulate a query?=
If you can’t understand the documents…
How do you know something <= span style=3D'font-family:Arial;mso-ascii-font-family:Arial;mso-hansi-font-fami= ly: Arial;font-size:67%;color:red'>is worth looking at?
How can you understand the <= span style=3D'font-family:Arial;mso-ascii-font-family:Arial;mso-hansi-font-fami= ly: Arial;font-size:67%;color:red'>retrieved documents?
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Early Work
= 226;1964 International Road Research
&= #8211;Multilingual thesauri
= 226;1970 SMART
&= #8211;Dictionary-based free-text cross-language retrieval
= 226;1978 ISO Standard 5964 (revised 1985)
&= #8211;Guidelines for developing multilingual thesauri
= 226;1990 Latent Semantic Indexing
&= #8211;Corpus-based free-text translingual retrieval
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Multilingual Thesauri
&#= 8226;Build a cross-cultural knowledge structure
&= #8211;Cultural differences influence indexing choices
&#= 8226;Use language-independent descriptors
&= #8211;Matched to language-specific lead-in vocabulary
&#= 8226;Three construction techniques
&= #8211;Build it from scratch
&= #8211;Translate an existing thesaurus
&= #8211;Merge monolingual thesauri
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Translingual Retrieval Architectur= e
Language <= /div>
Identification=
English
Term
Selection
Chinese
Term <= /div>
Selection<= /div>
Cross-
Language
Retrieval
Monolingual <= /span>
Chinese
Retrieval<= /div>
3: 0.91
4: 0.57
5: 0.36
1: 0.72
2: 0.48
Chinese
Query
Chinese
Term <= /div>
Selection<= /div>
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file:///C:/B278E252/796f0712_files/slide0267.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Evidence for Language Identificati= on
&#= 8226;Metadata
&= #8211;Included in HTTP and HTML
• <= /div>
&#= 8226;Word-scale features
&= #8211;Which dictionary gets the most hits?
• <= /div>
&#= 8226;Subword features
&= #8211;Character n-gram statistics
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Query-Language IR
English =
queries
Chinese Document
Collection
Retrieval
 Engine
Translation
System
English Document
Collection
Results<= /b>
select
examine<= /i>
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Example: Modular use of MT
•Select a = single query language
•
<= span class=3DBB style=3D'position:absolute;left:-3.93%'>•Translate= every document into that language
•
•Perform monolingual retrieval
•
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TDT-3 Mandarin Broadcast News
Systr= an
Balan= ced 2-best translation
Is Machine Translation Enough?
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Query vs. Document Translation
&#= 8226;Query translation
&= #8211;Efficient for short queries (not relevance feedback)
&= #8211;Limited context for ambiguous query terms
&#= 8226;Document translation
&= #8211;Rapid support for interactive selection
&= #8211;Need only be done once (if query language is same)
&#= 8226;Merged query and document translation
&= #8211;Can produce better effectiveness than either alone
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Interlingual Retrieval
Interlingual
Retrieval
3: 0.91
4: 0.57
5: 0.36
Query =
Translation
Chinese
Query =
Terms
English
Document
Terms
Document
Translation
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Learning From Document Pairs
  E1    E2     E3      E4    E5      S1     S2    S3      S4=
Doc 1
Doc 2
Doc 3
Doc 4
Doc 5
4
2
2
1
8
4
4
2
2
2
2
1
2
1
2
1
4
1=
2
1
English Terms
Spanish Terms
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Generalized Vector Space Model
&#= 8226;“Term space” of each language is different
&= #8211;Document links define a common “document space”
– <= /div>
&#= 8226;Describe documents based on the corpus
&= #8211;Vector of similarities to each corpus document
– <= /div>
&#= 8226;Compute cosine similarity in document space
– <= /div>
&#= 8226;Very effective in a within-domain evaluation
------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0224.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Latent Semantic Indexing
= 226;Cosine similarity captures noise with signal
&= #8211;Term choice variation and word sense ambiguity
– <= /div>
&#= 8226;Signal-preserving dimensionality reduction
&= #8211;Conflates terms with similar usage patterns
&#= 8226;Reduces term choice effect, even across languages
– <= /div>
&#= 8226;Computationally expensive
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oil
petroleum
probe
survey
take samples
Which
translation?
No
translation!
restra= in
oil
petroleum
probe
survey
take samples
cymbidium
goeringii
Wrong
segmentation
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What’s a “Term?”
= 226;Granularity of a “term” depends on the task
&= #8211;Long for translation, more fine-grained for retrieval =
&#= 8226;Phrases improve translation two ways
&= #8211;Less ambiguous than single words
&= #8211;Idiomatic expressions translate as a single concept
&#= 8226;Three ways to identify phrases
&#= 8211;Semantic        = ;  (e.g., appears in a dictionary)
&= #8211;Syntactic        = ;  (e.g., parse as a noun phrase)
&= #8211;Co-occurrence (appear together unexpectedly often)
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Learning to Translate
&#= 8226;Lexicons
&= #8211;Phrase books, bilingual dictionaries, …
– <= /div>
&#= 8226;Large text collections
&= #8211;Translations (“parallel”)
&= #8211;Similar topics (“comparable”)
»
&#= 8226;Similarity
&= #8211;Similar pronunciation
»
&#= 8226;People
Fundamentally, there are four sources of knowledge that we can rely on when teaching a machine to translate.  Perha= ps the simplest is some form of dictionary.&nbs= p; Dictionaries are very useful, but it is hard for machines to learn= to select the right translation using a dictionary alone because the machine= has no real sense of context.  L= arge collections of text can provide that context, however, and in recent years they have proven to be very useful as a basis for building “machine translation” systems.  The best results have been obtained using very large collections of translated documents, which we call a “parallel text collection”.  The next two slides illustrate h= ow that is done.
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Types of Lexical Resources
&#= 8226;Ontology
&= #8211;Organization of knowledge
&#= 8226;Thesaurus
&= #8211;Ontology specialized to support search
&#= 8226;Dictionary
&= #8211;Rich word list, designed for use by people
&#= 8226;Lexicon
&= #8211;Rich word list, designed for use by a machine
&#= 8226;Bilingual term list
&= #8211;Pairs of translation-equivalent terms
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R= 26;Original query: El Nino and infectious diseases
= 226; =
R= 26;Term selection: “El Nino” infectious diseases
= 226; =
R= 26;Term translation:<= span style=3D'mso-tab-count:1;width:3.4%'>
= 211; (Dictionary coverage: “El Nino” is not found)
= 226;
R= 26;Translation select= ion: =
= 226; =
R= 26;Query formulation:= =
= 211;Structure: =
Dictionary-Based Query Translation =
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Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlh/QAdAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAAD7 ABsAgAAAADMzzALKhI+py+0PIwhB2oszo7r7D4biwY3m2ZToyras6sYhLNf2PVX4jtH8D8z4gsSE rohMko7KZs4J3Q2jxCn1CrJig9qtF9L98sLi8tPsJKOx6jWu7U7C47c5/We/2/L6V4XfV8MBGJhF wVQIdYiYKHjYeLXICNkiSam4eCnzqBlJ2LkwCRolOqrxZ8pWmiqhssqKZ/AKq8CJkEkLBGPLJen7 Cxws7BsxbHyM/CmUzGy50Qz9PJu7PG1oumtN7aGcQju4XfdCjRouOE5eAAA7 ------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0487.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Four-Stage Backoff
•Tralex might contain stems, surface forms, or some combination of the two.
mangez=
mangez=
mangez<= /div>
mange
mange
mangez<= /div>
mange
mange
mangez<= /div>
mange
mangent=
mange
- eat
- eats
eat
- eat
- eat
Docu= ment
Tran= slation Lexicon
surface form
surface form
stem
surface form
surface form
stem
stem
stem
French stemmer: Oard, Levow, and Cabezas (2001); English: Inquiry’s kstem
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Results
STRAND corpus tralex (N=3D1)
0.2320<= /div>
STRAND corpus tralex (N=3D2)
0.2440=
STRAND corpus tralex (N=3D3)
0.2499=
Merging= by voting
0.2892=
Baseline: downloaded dictionary
0.2919<= /div>
= Backoff from dictionary to corpus tralex
0.3282
Cond= ition
Mean Average Precision
+12% (p < .01) relative
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Results Detail
DmAP
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Exploiting Part-of-Speech (POS)
<= span style=3D'font-size:133%'>•Constrain= translations by part-of-speech
<= span style=3D'font-size:117%'>–Requires = POS tagger and POS-tagged lexicon
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<= span style=3D'font-size:133%'>•Works wel= l when queries are full sentences
<= span style=3D'font-size:117%'>–Short que= ries provide little basis for tagging
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<= span style=3D'font-size:133%'>•Constrain= ed matching can hurt monolingual IR
<= span style=3D'font-size:117%'>–Nouns in queries often match verbs in documents
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The Short Query Challenge
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Sourc= e:  Jack Xu, Excite@Home, 1999=
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file:///C:/B278E252/796f0712_files/slide0477.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
“Structured Queries”
•<= /span>Weight of term a in a document i depends on:
–<= /span>TF(a,i= ): Frequency of term a in document = i
–<= /span>DF(a):   How many documents term a <= span style=3D'font-size:86%'>occurs in
–
•<= /span>Build p= seudo-terms from alternate translations
–<= /span>TF (syn(a,b),i) =3D TF(a= ,i)+TF(b,i)
–DF (syn(a,b) =3D |{docs with a}U{docs with = b}|= 3;
–
•<= /span>Downweight terms with any common translation= 3;
–<= /span>Particularly effective for long queries
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(Query Terms:   1:        = ;      2:     &n= bsp;            3:      )
Computing Weights
•Unbalanced:
–Overweights query terms that have many translation= s
–<= /span>
•Balanced (#sum):
–Sensitive to rare translations <= /div>
–<= /span>
•Pirkola (#syn):
–Deemphasizes query terms with any co= mmon translation
= 226;
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Ranked
 Retrieval
English/English
Translation
Lexicon
Measuring Coverage Effects
Ranked
List
113,000
CLEF English
News Stories
CLEF
Relevance
Judgments
Evaluation
Meas= ure of Effectiveness
33 English Queries (TD)
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35 Bilingual Term Lists
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Chinese (= 193, 111)
<= span class=3DHBB style=3D'position:absolute;left:-8.29%'>•German (= 103, 97, 89, 6)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Hungarian (63)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Japanese (54)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Spanish (= 35, 21, 7)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Russian (= 32)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Italian (= 28, 13, 5)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•French (2= 0, 17, 3)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Esperanto (17)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Swedish (= 10)
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Dutch (10= )
<= span class=3DHBB style=3D'position:absolute;left:-9.7%'>•Norwegian= (6)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Portugu= ese (6)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Greek (= 5)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Afrikaa= ns (4)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Danish = (4)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Iceland= ic (3)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Finnish (3)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Latin (= 2)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Welsh (= 1)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Indones= ian (1)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Old Eng= lish (1)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Swahili (1)
<= span class=3DHBB style=3D'position:absolute;left:-10.36%'>•Eskimo = (1)
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7% OOV
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Out-of-Vocabulary Distribution
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Measuring Named Entity Effect
Compute=
Term Weights
Build Index
Englis= h
Docume= nts
Comput= e
Term Weights
Comput= e
Document Score
Sort Scores
Ranked
List
Englis= h
Query
Translation
Lexicon
- Named =
Entities
+ Named
Entities
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Named entities removed
Named entities from term list
Named entities added
Full Query
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Hieroglyphic
Egyptian Demotic
Greek
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Types of Bilingual Corpora
&#= 8226;Parallel corpora: translation-equivalent pairs
&#= 8211;Document pairs
&#= 8211;Sentence pairs 
&#= 8211;Term pairs     
• <= /div>
&#= 8226;Comparable corpora: topically related
&#= 8211;Collection pairs
&#= 8211;Document pairs
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Exploiting Parallel Corpora
•
•Automatic acquisition = of translation lexicons
•<= /span>
•Statistical machine translation
•
•Corpus-guided translation selection= 3;
•<= /span>
•Document-linked techniques =
•
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Some Modern Rosetta Stones
&#= 8226;News:
&= #8211;DE-News (German-English)
&= #8211;Hong-Kong News, Xinhua News (Chinese-English)
&#= 8226;Government:
&= #8211;Canadian Hansards (French-English)
–Europarl (Danish, Dutch, English, Finnish, French, German, Greek, Italian, Portugese, Spanish, Swedish)
&= #8211;UN Treaties (Russian, English, Arabic, …)
&#= 8226;Religion
&= #8211;Bible, Koran, Book of Mormon
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Parallel Corpus
•Example f= rom DE-News (8/1/1996)
•
Diverging opinions about planned tax reform
Unterschiedliche Meinungen zur geplanten Steuerreform<= span style=3D'font-family:Arial;font-size:67%'>
The discussion around the envisaged major tax reform continue= s .
Die Diskussion um die vorgesehene grosse Steuerreform dauert an .
The FDP economics expert , Graf Lambsdorff , to= day came out in favor of advancing the enactment of significant parts of the overhaul , currently planned for 1999 .
Der FDP - Wirtschaftsexperte Graf Lambsdorff sp= rach sich heute dafuer aus , wesentliche Teile der fuer 1999 geplanten Reform= vorzuziehen .=
English:
German:
English:
German:
English:
German:
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Word-Level Alignment
Diverging opinions about planned tax reform
Unterschiedliche Meinungen zur geplanten Steuerreform
English
German
Madam President , I had asked the administration …
English
Señora Presidenta, había pedi= do a la administración del Parlamento …
Spanish
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A Translation Model
•From word-aligned bilingual text, we induce a translation model
•
•Example:&= #13;
•
where,
p(探测|survey) =3D 0.4 <= /span>
p(试探|survey) =3D 0.3
p(测量|survey) =3D 0.25
p(样品|survey) =3D 0.05
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Using Multiple Translations
&#= 8226;Weighted Structured Query Translation
R= 11;Takes advantage of multiple translations and translation probabilities
= 226;TF and DF of query term e are computed using TF and DF of its translations:
• <= /div>
–
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Evaluating Corpus-Based Techniques=
&#= 8226;Within-domain evaluation (upper bound)
&= #8211;Partition a bilingual corpus into training and test
&= #8211;Use the training part to tune the system
&= #8211;Generate relevance judgments for evaluation part
• <= /div>
&#= 8226;Cross-domain evaluation (fair)
&= #8211;Use existing corpora and evaluation collections
&= #8211;No good metric for degree of domain shift
------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0521.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Ranked Retrieval Effectiveness
English queries, Arabic documents
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Exploiting Comparable Corpora
•Blind relevance feedback
–Existing CLIR techniqu= e + collection-linked corpus
–<= /span>
•Lexicon enrichment = ;
–Existing lexicon + collection-linked corpus
–<= /span>
•Dual-space techniques&= #13;
–Document-linked corpus=
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Bilingual Query Expansion
source language query
Query
Translation
results
Source
Language
IR
Target
Language
IR
source language
collection
target language
collection
expanded = ;
source language
query
expanded = ;
target language
terms
Pre-translation expansion
Post-translation expansion
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Query Expansion Effect
Paul McNamee and James Mayfield, SIGIR-2002
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Blind Relevance Feedback
&#= 8226;Augment a representation with related terms
&= #8211;Find related documents, extract distinguishing terms
– <= /div>
&#= 8226;Multiple opportunities:
&= #8211;Before doc translation: Enrich= the vocabulary
&= #8211;After doc translation: Mitiga= te translation errors
&= #8211;Before query translation: Impr= ove the query
&= #8211;After query translation: Miti= gate translation errors
– <= /div>
&#= 8226;Short queries get the most dramatic improvement
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Post-Translation “Document Expansion”
Mandarin Chinese Document= s
Term-to-Term
Translation
English
Corpus
IR
System
Top 5
Automatic
Segmentation
Term
Selection
IR
System
Results
English
Query
Docume= nt to be Indexed
Single Document
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Why Document Expansion Works
&#= 8226;Story-length objects provide useful context
»
&#= 8226;Ranked retrieval finds signal amid the noise
»
&#= 8226;Selective terms discriminate among documents
&#= 8211;Enrich index with low DF terms from top documents
»
&#= 8226;Similar strategies work well in other applications
&#= 8211;CLIR query translation
&#= 8211;Monolingual spoken document retrieval
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Lexicon Enrichment
= 230; Cross-Language Evaluation Forum …
= 230; Solto Extunifoc Tanixul Knadu …
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Lexicon Enrichment
&#= 8226;Use a bilingual lexicon to align “context regions”
&= #8211;Regions with high coincidence of known translations
– <= /div>
&#= 8226;Pair unknown terms with unmatched terms
&= #8211;Unknown: language A, not in the lexicon
&= #8211;Unmatched: language B, not covered by translation
– <= /div>
&#= 8226;Treat the most surprising pairs as new translations
–
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Cognate Matching
&#= 8226;Dictionary coverage is inherently limited
&= #8211;Translation of proper names
&= #8211;Translation of newly coined terms
&= #8211;Translation of unfamiliar technical terms
– <= /div>
&#= 8226;Strategy: model derivational translation
&= #8211;Orthography-based
&= #8211;Pronunciation-based
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Matching Orthographic Cognates
&#= 8226;Retain untranslatable words unchanged
&#= 8211;Often works well between European languages
– <= /div>
&#= 8226;Rule-based systems
&= #8211;Even off-the-shelf spelling correction can help!
– <= /div>
&#= 8226;Character-level statistical MT
&= #8211;Trained using a set of representative cognates
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Matching Phonetic Cognates
&#= 8226;Forward transliteration
&= #8211;Generate all potential transliterations
– <= /div>
&#= 8226;Reverse transliteration
&= #8211;Guess source string(s) that produced a transliteration
– <= /div>
&#= 8226;Match in phonetic space
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Leveraging Cognates
String
Comparison
Written
Form
Written
Form
Alphabetic
Transliteration
Pronunciation
Phonetic
Transliteration
Pronunciation
Spoken
Form
Spoken
Form
Phonetic
Comparison
Similarity
Similarity
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Cross-Language “Retrieval̶= 1;
Search<= /div>
Translated Query
Ranked List
Query
Translation
Query
The answer can be given by looking at interactions within the search process monolingual or multilingual.

Besides interested in nominate, interactive ir also interested in the three yellow boxes in predict and choose
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Interactive Translingual Search
Search<= /div>
Translated Query
Selection
Ranked List
Examination
Document
Use
Document
Query
Formulation
Query
Translation
Query
Query Reformulation
MT
Translated “Headlines”
English Definitions
The answer can be given by looking at interactions within the search process monolingual or multilingual.

Besides interested in nominate, interactive ir also interested in the three yellow boxes in predict and choose
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Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Selection
&#= 8226;Goal: Provide information to support decisions
• <= /div>
&#= 8226;May not require very good translations
&= #8211;e.g., Term-by-term title translation
• <= /div>
&#= 8226;People can “read past” some ambiguity
&= #8211;May help to display a few alternative translations
------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0301.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Language-Specific Selection
Swiss bank
Qu= ery in English:
Search
English&#= 13;
German= 3;
(Swiss)
(Bankgebäude, bankverbindung, bank)&#= 13;
1 (0.72) Swiss Bankers Criticized
AP / June 14, 1997
2 (0.48) Bank Director Resigns
AP / July 24, 1997
1 (0.91) U.S. Senator Warpa= thing
NZZ / June 14, 1997
2 (0.57) [Bankensecret] Law Change
SDA / August 22, 1997
3 (0.36) Banks Pressure Existent
NZZ / May 3, 1997
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Translingual Selection
Swiss bank
Qu= ery in Eng= lish:
Search
German Query:
(Swiss)
(Bankgebäude, bankverbindung, bank)&#= 13;
1 (0.91) U.S. Senator Warpathing NZZ June 14, 1997
2 (0.57) [Bankensecret] Law Change SDA August 22, 1997 <= /div>
3 (0.52) Swiss Bankers Criticized AP June 14, 1997
4 (0.36) Banks Pressure Exi= stent NZZ May 3, 1997
5 (0.28) Bank Director Resigns AP July 24, 1997&#= 13;
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Merging Ranked Lists
= •Types of Evidence
= –Rank
= –Score
– =
&= #8226;Evidence Combination
= –Weighted round robin
= –Score combination
– =
= •Parameter tuning
= –Condition-based
= –Query-based
     1  voa4062  .22
     2  voa3052  .21
     3  voa4091  .17
  …
1000  voa4221 .04
     1  voa4062  .52
     2  voa2156  .37
     3  voa3052  .31
  …
1000  voa2159 .02
     1 voa4062 <= /div>
     2  voa3052
     3  voa2156
  …
1000  voa4201
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Examination Interface
&#= 8226;Two goals
&= #8211;Refine document delivery decisions
&= #8211; Support vocabulary discovery for q= uery refinement
– <= /div>
&#= 8226;Rapid translation is essential
&= #8211;Document translation retrieval strategies are a good fit
&= #8211;Focused on-the-fly translation may be a viable alternative
------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0156.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Uh oh…
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Translation for Assessment
•  =   Indonesian City of Bali in October last year in the bomb blast= in the case= of imam accused India of the sea on Monday began to be averted. The attack on getting and its plan to make the charges and decide if it were fou= nd guilty, he death sentence of May. Indonesia of the police sa= id that the imam sea bomb blasts in his hand claim to be accepted. A= night Cl= ub and time = in the in more than 200 people were killed and several injured were in <= /span>which most for= eign nationals. …
Here is a translation from the best Hindi-to-English machine translation system in the previous slide.  The translation is certainly not good enough to read for understanding, but t= here is probably enough there to allow a searcher to decide whether it would be worth paying someone to make a fluent translation.  From the highlighted words, we c= an see that there was an attack using a bomb in a Bali night club and that many people were killed.  Pulling= that information out of an imperfect translation such as this takes some time,= of course.  But imagine how much longer it would take if you were looking at a Hindi document and did not = know Hindi.  Thirty days before t= his translation was produced, we were not able to find a single translation system anywhere in the world to translate Hindi into English.  Perhaps even more impressively, = the person that did the majority of the work to build this system spoke no Hi= ndi at all!  It used to take ten= years and an army of linguists to build a mediocre machine translation system.<= span style=3D'mso-spacerun:yes'>  We can now build systems that ar= e just as good in a few months, and this technology has a clear potential for further improvement.
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MT in a Month
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Here is one approach that we have been experimenting with.  At the top of the screen, you ca= n see a query that was entered by the searcher: “Indian film and social a= nd cultural impact.”  Our system knows six Hindi translations for “film”, which are sho= wn on the six lines of the table in the upper right.  In the column labeled “Hin= di” we show a locally developed transliteration that is similar to ITRANS.  English speakers sometimes find = this provides useful cues to meaning, as is the case in the bottom line with “sainaemaaa,” which sounds like the English word “cinema.”  In ot= her cases, automaticaly detected synonyms are useful, as in the case in the fourth line where “membrane” indicates a different meaning for “film.”  The sea= rcher can deselect undesired translations and then search again.  The remainder of the system work= s like any Web search engine, although we clearly have a ways to go before our interface is as elegant as Google.  = As with the translation system, we adapted this system to Hindi in a month.<= /font>
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file:///C:/B278E252/796f0712_files/slide0451.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Experiment Design
Partici= pant
1
2
3
4
Task Order
Narr= ow:
Broa= d:
Topic Key
System Key
Syste= m B:
Syste= m A:
Topic11, Topic17
Topic13, Topic29
Topic11, Topic17
Topic13, Topic29
Topic17, Topic11
Topic29, Topic13
Topic17, Topic11
Topic29, Topic13
11, 13
17, 29
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Maryland Experiments
•<= /span>MT is almost always better
–<= /span>Significant overall and for narrow topics alone (one-tailed t-test, p<0.05)
•= 3;
•<= /span>F measure is less insightful for narrow topics = ;
–<= /span>Always near 0 or 1
|---------- Broad topics -----------|
|--------- Narrow topics -----------|
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iCLEF 2002 Evaluation
Engl= ish Queries
Germ= an Documents
20 minutes/topic
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Better Mental Process Models
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3D"Text=
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with PRISE
Delivery
&#= 8226;Use may require high-quality translation
&= #8211;Machine translation quality is often rough
• <= /div>
&#= 8226;Route to best translator based on:
&= #8211;Acceptable delay
&= #8211;Required quality (language and technical skills)
&= #8211;Cost
------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0524.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Where Things Stand
&#= 8226;Ranked retrieval works well across languages
&= #8211;Bonus: easily extended to text classification
&= #8211;Caveat: mostly demonstrated on news stories
– <= /div>
&#= 8226;Machine translation is okay for niche markets
&= #8211;Keep an eye on this: accuracy is improving fast
– <= /div>
&#= 8226;Building explainable systems seems possible
------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0509.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Recap: Finding What You Can’t Read
&#= 8226;Three key challenges
&= #8211;Segmentation, coverage, evidence combination
– <= /div>
&#= 8226;Segmentation objectives differ
&= #8211;Translation: Favor precision over coverage
&= #8211;Retrieval: Balance precision and recall=
»
&#= 8226;Multiple coverage enhancement techniques
&= #8211;Expansion, backoff translation, cognate matching
»
&#= 8226;Translating evidence beats translating weights
------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/slide0039.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Translingual Topic Tracking with PRISE
Research Opportunities
<= ![endif]>
Segmentation &
Phrase Indexing = ;
= Lexical
Coverage
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Until the year 2000, more than h= alf of all users of the Internet spoke English as their native language.  Although the total number of Engl= ish speakers on the Internet continues to increase, the number of Internet use= rs that speak a first language other than English is rising far more rapidly.  The consulting firm Global Reach estimates that more that two-thirds of all Internet users presently speak a first language other than English.
However, English still dominates= the information space.  As the in= ner ring illustrates, more than two-thirds of all Web pages are still written = in English.  The same is true in= our libraries; English is the principal language of international publishing.<= span style=3D'mso-spacerun:yes'>  In business, English is the langu= age of commerce.  For these reasons,= many people around the world have a working knowledge of English as a second language.  But many others do not.  If we aspire to univers= al access, we must build systems that help all of our citizens to access the = full storehouse of the world’s information. In my talk this morning, I wi= ll review what we presently know how to do.&= nbsp; I’ll then close with a few remarks about how we might employ these capabilities.
This chart shows the 15 n= ations with at least 100 billion dollars in annual imports and exports.
Together, these nations a= ccount for 73% of the world’s exports
World trade thus defines = nine major languages:
English, German, Japanese, Chinese, French, Italian, Dutch, Korean, Spanish
There are three key drive= rs that decide which languages get attention.
1)Where is the money.  The G7 languages are = well covered
2)Where are the people.  This seems to have a= much smaller effect.
3)Where are the problems:  This explains the interest in Farsi, Korean, etc.
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Fundamentally, there are four so= urces of knowledge that we can rely on when teaching a machine to translate.  Perhaps the simplest is some form= of dictionary.  Dictionaries are= very useful, but it is hard for machines to learn to select the right translati= on using a dictionary alone because the machine has no real sense of context.  Large collections o= f text can provide that context, however, and in recent years they have proven to= be very useful as a basis for building “machine translation” systems.  The best results ha= ve been obtained using very large collections of translated documents, which = we call a “parallel text collection”.  The next two slides illustrate ho= w that is done. 
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The answer can be given by looki= ng at interactions within the search process monolingual or multilingual.
Besides interested in nominate, interactive ir also interested in the three yellow boxes in predict and choose
The answer can be given by looki= ng at interactions within the search process monolingual or multilingual.
Besides interested in nominate, interactive ir also interested in the three yellow boxes in predict and choose
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Here is a translation from the b= est Hindi-to-English machine translation system in the previous slide.  The translation is certainly not = good enough to read for understanding, but there is probably enough there to al= low a searcher to decide whether it would be worth paying someone to make a fl= uent translation.  From the highli= ghted words, we can see that there was an attack using a bomb in a Bali night cl= ub and that many people were killed.  Pulling that information out of an imperfect translation such as th= is takes some time, of course.  = But imagine how much longer it would take if you were looking at a Hindi docum= ent and did not know Hindi.  Thir= ty days before this translation was produced, we were not able to find a sing= le translation system anywhere in the world to translate Hindi into English.<= span style=3D'mso-spacerun:yes'>  Perhaps even more impressively, t= he person that did the majority of the work to build this system spoke no Hin= di at all!  It used to take ten = years and an army of linguists to build a mediocre machine translation system.  We can now build systems that are= just as good in a few months, and this technology has a clear potential for fur= ther improvement. 
Here is one approach that we hav= e been experimenting with.  At the t= op of the screen, you can see a query that was entered by the searcher: “Indian film and social and cultural impact.”  Our system knows six Hindi transl= ations for “film”, which are shown on the six lines of the table in t= he upper right.  In the column l= abeled “Hindi” we show a locally developed transliteration that is similar to ITRANS.  English s= peakers sometimes find this provides useful cues to meaning, as is the case in the= bottom line with “sainaemaaa,” which sounds like the English word “cinema.”  In oth= er cases, automaticaly detected synonyms are useful, as in the case in the fo= urth line where “membrane” indicates a different meaning for “film.”  The sear= cher can deselect undesired translations and then search again.  The remainder of the system works= like any Web search engine, although we clearly have a ways to go before our in= terface is as elegant as Google. J  As with the translation system, we adapted this system to Hindi in a month.
Shrink a search session to half,= 10 minutes, obeserve the effect to search with translations aids
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_RSW() if( IsWin("PPTSld") && parent.IsFullScrMode() ) FullScrInit(); =09 MakeSldVis(); ChkAutoAdv() if( runAnimations ) { if( document.all("NSPlay") ) document.all("NSPlay").autoStart =3D false; if( sld.filters && sld.filters.revealtrans ) setTimeout( "document.body.start()", sld.filters.revealtrans.duration * = 1000 ); else document.body.start(); } } function MakeSldVis()=20 { var fTrans=3Dg_showAnimation && SldHasTrans() if( fTrans )=09 { if( g_bgSound ) { idx=3Dg_bgSound.indexOf(","); pptSound.src=3Dg_bgSound.substr( 0, idx ); pptSound.loop=3D -(parseInt(g_bgSound.substr(idx+1))); } SlideObj.filters.revealtrans.Apply()=09 } SlideObj.style.visibility=3D"visible" if( fTrans ) SlideObj.filters.revealtrans.Play() } function MakeNotesVis()=20 { if( !IsNts() ) return false=20 SlideObj.style.display=3D"none" nObj =3D document.all.item("NotesObj") parent.SetHasNts(0) if( nObj ) {=20 nObj.style.display=3D"" parent.SetHasNts(1) } return 1 } function ChkAutoAdv() { if(SldHasTrans()) SlideObj.onfilterchange=3DAutoAdv else AutoAdv() } function AutoAdv() { if(!IsWin("PPTSld") || !gUseSldTimings )return var sld=3DGetCurSld() if( (sld.mAdvDelay>0) && !parent.IsFramesMode() ) setTimeout("parent.GoToNextSld()",sld.mAdvDelay) } function GetObj(id) { if(g_supportsPPTHTML) return document.all(id); else return document.getElementById(id); } function SldHasTrans() { return SlideObj.style.filter !=3D ""; } function GetSldId() { return sId=3Dlocation.href.substring(location.href.la= stIndexOf('/')+1) } function HideMenu() { if( frames["PPTSld"] && PPTSld.document.all.item("ctx= tmenu") && PPTSld.ctxtmenu.style.display!=3D"none" ) { PPTSld.ctxtmenu.styl= e.display=3D'none'; return true } return false } function IsWin( name ) { return window.name =3D=3D name } function IsNts() { return IsWin("PPTNts") } function IsSldOrNts() { return( IsWin("PPTSld")||IsWin("PPTNts") ) } function SupportsPPTAnimation() { return( navigator.platform =3D=3D "Win32"= && navigator.appVersion.indexOf("Windows")>0 ) } function SupportsPPTHTML() { var appVer=3Dnavigator.appVersion, msie=3DappVer.indexOf("MSIE "), ver=3D0 if( msie >=3D 0 ) ver=3DparseFloat( appVer.substring( msie+5, appVer.indexOf(";",msie) ) ) else ver=3DparseInt(appVer) return( ver >=3D 4 && msie >=3D 0 ) } function _RSW() { if( !g_supportsPPTHTML || IsNts() || ( !g_scaleInFrame && (!IsWin("PPTSld") || !parent.IsFullScrMode()) ) ) return var padding=3D0; if( IsWin("PPTSld") && parent.IsFramesMode() ) padding=3D6 cltWidth=3Ddocument.body.clientWidth-padding cltHeight=3Ddocument.body.clientHeight-padding factor=3D(1.0*cltWidth)/g_origW if( cltHeight < g_origH*factor ) factor=3D(1.0*cltHeight)/g_origH newSize =3D g_origSz * factor if( newSize < 1 ) newSize=3D1 s=3DSlideObj.style s.fontSize=3DnewSize+"px" s.posWidth=3Dg_origW*factor s.posHeight=3Dg_origH*factor s.posLeft=3D(cltWidth-s.posWidth+padding)/2 s.posTop=3D(cltHeight-s.posHeight+padding)/2 if( g_scaleHyperlinks ) ScaleHyperlinks( factor ) } function _InitAnimations() { animRuntimeInstalled =3D ''+document.body.localTime !=3D 'undefined'; isFullScreen =3D (window.name =3D=3D "PPTSld") && !parent.IsFramesMode(); g_animUseRuntime =3D g_showAnimation && animRuntimeInstalled && !(isFullSc= reen && parent.IsSldVisited()); if( g_animUseRuntime ) { collSeq =3D document.all.tags("seq"); if( collSeq !=3D null ) { for(ii=3D0;ii numSlds ) gSldJumpIdx =3D numSlds; if ( gSldJumpIdx >=3D 0 ) { if ( gSldJumpIdx =3D=3D 0 ) gSldJumpIdx =3D 1; var jumpTo =3D parseInt(gSldJumpIdx); gSldJump =3D 0; gSldJumpIdx =3D ""; win.GoToSld( parent.GetSldList().mList[jumpTo-1].mSldHref ) } } } function _KDH() { if( event.keyCode =3D=3D 8 ) { event.returnValue =3D 0; parent.GoToPrevSld(); } } var g_HLinkArray =3D new Array(); =20 function IMapAreaObj( areaObj, coords ) { this.areaObj =3D areaObj; this.coords =3D coords; } function InitHLinkArray() { var appVer =3D navigator.appVersion; var msie =3D appVer.indexOf ( "MSIE " ) var ver =3D 0; if ( msie >=3D 0 ) ver =3D parseInt ( appVer.substring( msie+5 ) ); linkNum =3D 0; for (i=3D0; i 4 ) ) g_HLinkArray[linkNum++] =3D new IMapAreaObj( areaObj, ParseCoords( ar= eaObj.coords ) ); } } function ScaleHyperlinks( factor ) { =20 for ( ii=3D0; ii< g_HLinkArray.length; ii++) { coordsStr=3D""; imaObj =3D g_HLinkArray[ii]; for ( jj=3D0; jj < imaObj.coords.length-1; jj++ ) coordsStr +=3D (imaObj.coords[jj]*factor) + ","; coordsStr +=3D (imaObj.coords[jj]*factor); imaObj.areaObj.coords =3D coordsStr; } } function ParseCoords( coordsStr ) { var numArray =3D new Array(); var i =3D curPos =3D commaPos =3D 0; while ( ( commaPos =3D coordsStr.indexOf(",", curPos) ) !=3D -1 ) {=20 numArray[i++] =3D parseInt( coordsStr.substr( curPos, commaPos ) ); curPos =3D commaPos + 1; } numArray[i] =3D parseInt( coordsStr.substr( curPos ) ); return numArray; } function DocumentOnClick() { if( IsNts() || parent.HideMenu() ) return; if( ( g_allowAdvOnClick && (window.name=3D=3D"PPTSld") && !parent.IsFrames= Mode() ) || (event && event.keyCode=3D=3D32) ) { =09 if( g_animUseRuntime && g_animMainSequence && g_animMainSequence.cangonex= t ) return; parent.GoToNextSld(); } } var g_supportsPPTHTML =3D SupportsPPTHTML(), g_scaleInFrame =3D 1, gId=3D""= , g_bgSound=3D"", g_scaleHyperlinks =3D false, g_allowAdvOnClick =3D 1, g_showInBrowser = =3D 0, gLoopCont =3D 0, gUseSldTimings =3D 1; var g_showAnimation =3D g_supportsPPTHTML && SupportsPPTAnimation() && ( (w= indow.name=3D=3D"PPTSld" && !parent.IsFramesMode()) || g_showInBrowser );va= r g_animManager =3D null; var g_animUseRuntime =3D false; var g_animItemsToHide, g_animInteractiveItems, g_animSlideTime; var g_animMainSequence =3D null; var ENDSHOW_MESG=3D"End of slide show, click to exit.", SCREEN_MODE=3D"Fram= es", gIsEndShow=3D0, NUM_VIS_SLDS=3D88, SCRIPT_HREF=3D"script.js", FULLSCR_= HREF=3D"fullscreen.htm"; var gCurSld =3D gPrevSld =3D 1, g_offset =3D 0, gNtsOpen =3D gHasNts =3D gO= tlTxtExp =3D 0, gHasNarration =3D 0, gOtlOpen =3D true window.gPPTHTML=3DSupportsPPTHTML() var gMainDoc=3Dnew Array(new hrefList("slide0426.htm",1,-1,1),new hrefList(= "slide0470.htm",1,-1,1),new hrefList("slide0356.htm",1,-1,1),new hrefList("= slide0510.htm",1,-1,1),new hrefList("slide0511.htm",1,-1,1),new hrefList("s= lide0536.htm",1,-1,1),new hrefList("slide0169.htm",1,-1,1),new hrefList("sl= ide0188.htm",1,-1,1),new hrefList("slide0518.htm",1,-1,1),new hrefList("sli= de0190.htm",1,-1,1),new hrefList("slide0537.htm",1,-1,1),new hrefList("slid= e0040.htm",1,-1,1),new hrefList("slide0313.htm",1,-1,1),new hrefList("slide= 0315.htm",1,-1,1),new hrefList("slide0363.htm",1,-1,1),new hrefList("slide0= 193.htm",1,-1,1),new hrefList("slide0400.htm",1,-1,1),new hrefList("slide02= 66.htm",1,-1,1),new hrefList("slide0267.htm",1,-1,1),new hrefList("slide054= 1.htm",1,-1,1),new hrefList("slide0209.htm",1,-1,1),new hrefList("slide0038= .htm",1,-1,1),new hrefList("slide0540.htm",1,-1,1),new hrefList("slide0270.= htm",1,-1,1),new hrefList("slide0271.htm",1,-1,1),new hrefList("slide0324.h= tm",1,-1,1),new hrefList("slide0326.htm",1,-1,1),new hrefList("slide0224.ht= m",1,-1,1),new hrefList("slide0526.htm",1,-1,1),new hrefList("slide0335.htm= ",1,-1,1),new hrefList("slide0513.htm",1,-1,1),new hrefList("slide0473.htm"= ,1,-1,1),new hrefList("slide0474.htm",1,-1,1),new hrefList("slide0487.htm",= 1,-1,1),new hrefList("slide0492.htm",1,-1,1),new hrefList("slide0493.htm",1= ,-1,1),new hrefList("slide0480.htm",1,-1,1),new hrefList("slide0172.htm",1,= -1,1),new hrefList("slide0477.htm",1,-1,1),new hrefList("slide0478.htm",1,-= 1,1),new hrefList("slide0528.htm",1,-1,1),new hrefList("slide0529.htm",1,-1= ,1),new hrefList("slide0530.htm",1,-1,1),new hrefList("slide0533.htm",1,-1,= 1),new hrefList("slide0534.htm",1,-1,1),new hrefList("slide0535.htm",1,-1,1= ),new hrefList("slide0046.htm",1,-1,1),new hrefList("slide0323.htm",1,-1,1)= ,new hrefList("slide0483.htm",1,-1,1),new hrefList("slide0544.htm",1,-1,1),= new hrefList("slide0545.htm",1,-1,1),new hrefList("slide0546.htm",1,-1,1),n= ew hrefList("slide0548.htm",1,-1,1),new hrefList("slide0549.htm",1,-1,1),ne= w hrefList("slide0355.htm",1,-1,1),new hrefList("slide0521.htm",1,-1,1),new= hrefList("slide0045.htm",1,-1,1),new hrefList("slide0554.htm",1,-1,1),new = hrefList("slide0507.htm",1,-1,1),new hrefList("slide0330.htm",1,-1,1),new h= refList("slide0522.htm",1,-1,1),new hrefList("slide0011.htm",1,-1,1),new hr= efList("slide0035.htm",1,-1,1),new hrefList("slide0425.htm",1,-1,1),new hre= fList("slide0292.htm",1,-1,1),new hrefList("slide0403.htm",1,-1,1),new href= List("slide0404.htm",1,-1,1),new hrefList("slide0405.htm",1,-1,1),new hrefL= ist("slide0508.htm",1,-1,1),new hrefList("slide0497.htm",1,-1,1),new hrefLi= st("slide0498.htm",1,-1,1),new hrefList("slide0338.htm",1,-1,1),new hrefLis= t("slide0301.htm",1,-1,1),new hrefList("slide0302.htm",1,-1,1),new hrefList= ("slide0397.htm",1,-1,1),new hrefList("slide0340.htm",1,-1,1),new hrefList(= "slide0156.htm",1,-1,1),new hrefList("slide0515.htm",1,-1,1),new hrefList("= slide0496.htm",1,-1,1),new hrefList("slide0516.htm",1,-1,1),new hrefList("s= lide0451.htm",1,-1,1),new hrefList("slide0467.htm",1,-1,1),new hrefList("sl= ide0503.htm",1,-1,1),new hrefList("slide0523.htm",1,-1,1),new hrefList("sli= de0341.htm",1,-1,1),new hrefList("slide0524.htm",1,-1,1),new hrefList("slid= e0509.htm",1,-1,1),new hrefList("slide0039.htm",1,-1,1)); /********************************************* Frameset functions These functions control slide navigation and state of the frameset. **********************************************/ function FullScrInit() { g_allowAdvOnClick =3D GetCurSld().mAdvOnClk document.body.style.backgroundColor=3D"black" document.oncontextmenu=3Dparent._CM; document.onkeydown =3D _KDH; document.ondragstart=3DCancel document.onselectstart=3DCancel self.focus() } function Redirect( frmId ) {=09 var str=3Ddocument.location.hash,idx=3Dstr.indexOf('#'), sId=3DGetSldId() if(idx>=3D0) str=3Dstr.substr(1); if( window.name !=3D frmId && ( sId !=3D str) ) { obj =3D GetObj("Main-File") window.location.href=3Dobj.href+"#"+sId return 1 } return 0 } var MHTMLPrefix =3D CalculateMHTMLPrefix();=20 function CalculateMHTMLPrefix() { if ( document.location.protocol =3D=3D 'mhtml:') {=20 href=3Dnew String(document.location.href)=20 Start=3Dhref.indexOf('!')+1=20 End=3Dhref.lastIndexOf('/')+1=20 if (End < Start)=20 return href.substring(0, Start)=20 else=20 return href.substring(0, End)=20 } return ''; } function GetTags(base,tag) { if(g_supportsPPTHTML) return base.all.tags(tag); else return base.getElementsByTagName(tag); } function UpdNtsPane(){ if(frames["PPTNts"]) PPTNts.location.replace( MHTMLP= refix+GetHrefObj( gCurSld ).mNtsHref ) } function UpdNavPane( sldIndex ){ if(gNavLoaded) PPTNav.UpdNav() } function UpdOtNavPane(){ if(gOtlNavLoaded) PPTOtlNav.UpdOtlNav() } function UpdOtlPane(){ if(gOtlLoaded) PPTOtl.UpdOtl() } function SetHasNts( fVal ) { if( gHasNts !=3D fVal ) { gHasNts=3DfVal UpdNavPane() } } function ToggleOtlText() { gOtlTxtExp=3D!gOtlTxtExp UpdOtlPane() } function ClearMedia() { // Clear any sounds playing before launching another browser window. Other= wise, // in fullscreen mode, you'll continue to hear the sound in the frames mod= e. if (PPTSld.pptSound) PPTSld.pptSound.loop =3D 0; } function FullScreen() {=20 if ( PPTSld.g_animUseRuntime ) PPTSld.document.body.pause(); ClearMedia(); var href =3D ( document.location.protocol =3D=3D 'mhtml:') ? FULLSCR_HREF = : FULLSCR_HREF+"#"+GetHrefObj(gCurSld).mSldHref; if(PPTNav.event.ctrlKey) { var w =3D (window.screen.availWidth * 1.0) / 2.0 var h =3D w * (PPTSld.g_origH * 1.0) / PPTSld.g_origW win =3D window.open( MHTMLPrefix+href,null,"toolbar=3D0,resizable=3D1,top= =3D0,left=3D0," + "width=3D"+ w + ",height=3D" + h ); if( win.document.body && PPTSld.g_animUseRuntime ) win.document.body.PPTSldFrameset=3Dwindow; } else { win =3D window.open( MHTMLPrefix+href,null,"fullscreen=3Dyes" ); if( win.document.body && PPTSld.g_animUseRuntime ) win.document.body.PPTSldFrameset=3Dwindow; } } function ToggleVNarration() { rObj=3DPPTSld.document.all("NSPlay") if( rObj && !PPTSld.g_animUseRuntime ) { if( (rObj.playState =3D=3D 1)||(rObj.playState =3D=3D 0) ) rObj.Play() else if( rObj.playState =3D=3D 2 ) rObj.Pause() else return; } else if( PPTSld.g_animUseRuntime ) { narObj =3D PPTSld.document.all("narrationID") if( narObj ) narObj.togglePause() } } function GetCurSldNum() { =20 obj=3DGetHrefObj(gCurSld) if( obj.mOrigVis =3D=3D 1 ) return obj.mSldIdx else =20 return gCurSld } function GetNumSlds() { =20 if( GetHrefObj(gCurSld).mOrigVis =3D=3D 1 ) return GetSldList().mNumVisSlds; else return GetSldList().mList.length } function GetSldNum( href ) { for(ii=3D0; ii 1 ) PopSldList(); else if( !IsFramesMode() ) { if( gLoopCont ) GoToFirst() else EndShow() } } function GoToPrevSld() { ii=3DgCurSld-1 if( ii > 0 ) { obj=3DGetHrefObj(ii) while ( obj && ( obj.mVis =3D=3D 0 ) && ( ii>0 ) ) obj=3DGetHrefObj(--ii) if( ii =3D=3D 0 ) ii=3D1 GoToSldNum(ii) } } function GoToFirst(){ GoToSld( GetHrefObj(1).mSldHref ) } function GoToLast() { ii=3DGetSldList().mList.length if( ii !=3D gCurSld ) GoToSld( GetHrefObj(ii).mSldHref ) } function GoToSldNum( num ) { if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue obj =3D GetHrefObj( num ) obj.mVis=3D1 gPrevSld=3DgCurSld gCurSld =3D num; PPTSld.location.replace(MHTMLPrefix+obj.mSldHref) if( IsFramesMode() ) { UpdNavPane(); UpdOtlPane(); UpdNtsPane() } } function GoToSld( href ) { if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue GetHrefObj( GetSldNum(href) ).mVis=3D1 PPTSld.location.replace(MHTMLPrefix+href) } function SldUpdated( id ) { if( id =3D=3D GetHrefObj(gCurSld).mSldHref ) return gPrevSld=3DgCurSld gCurSld=3DGetSldNum(id) if( IsFramesMode() ) { UpdNavPane(); UpdOtlPane(); UpdNtsPane() } } function PrevSldViewed(){ GoToSld( GetHrefObj(gPrevSld).mSldHref ) } function HasPrevSld() { return ( gIsEndShow || ( gCurSld !=3D 1 && GetHrefO= bj( gCurSld-1 ).mVis =3D=3D 1 )||( GetCurSldNum() > 1 ) ) } function HasNextSld() { return (GetCurSldNum() !=3D GetNumSlds()) } function CloseWindow() { if( HideMenu() ) return; =09 var event =3D PPTSld.event; if( !IsFramesMode() && event && (event.keyCode=3D=3D27 || event.keyCode=3D= =3D32 || event.type=3D=3D"click" ) ) window.close( self ); CatchNumKeys( self, event ); } function Unload() { gIsEndShow=3D0; } function SetupEndShow() { gIsEndShow=3D1; PPTSld.document.body.scroll=3D"no"; PPTSld.document.onkeypress=3DCloseWindow; PPTSld.document.onclick=3DCloseWindow; PPTSld.document.oncontextmenu=3D_CM; } function EndShow() { if( IsFramesMode() ) return if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue doc=3DPPTSld.document var dir =3D doc.body.dir if( dir !=3D "rtl" ) dir =3D "ltr"; doc.open() doc.writeln('


' + ENDSHOW_MESG + '

') doc.close() } function SetSldVisited(){ GetSldList().mList[gCurSld-1].mVisited=3Dtrue } function IsSldVisited(){ return GetSldList().mList[gCurSld-1].mVisited } function hrefList( sldHref, visible, advDelay, advClk ) { this.mSldHref=3D this.mNtsHref =3D sldHref this.mOrigVis=3D this.mVis =3D visible this.mVisited=3D false this.mAdvDelay=3D advDelay this.mAdvOnClk=3D advClk } function SldList(arr,curSld,fEnd) { this.mCurSld =3D curSld; this.mList =3D new Array(); var idx =3D 1; for(ii=3D0;ii 0) { PushSldList(sldList,fEnd); gCurSld =3D 1; } else if( PPTSld.event ) PPTSld.event.cancelBubble=3Dtrue } function PushSldList(arr,fEnd) { var ii =3D gSldStack.length; gSldStack[ii] =3D new SldList(arr,gCurSld,fEnd); GoToSld( gSldStack[ii].mList[0].mSldHref ); } function PopSldList() { if (gSldStack[gSldStack.length-1].fEndShow) EndShow() else { gCurSld =3D gSldStack[gSldStack.length-1].mCurSld; gSldStack[gSldStack.length-1] =3D null; gSldStack.length--; var sldList =3D gSldStack[gSldStack.length-1]; GoToSld( sldList.mList[gCurSld - 1].mSldHref ); } } var custShowList=3Dnew Array(); /********************************************* Navigation button implementation There are 2 types of buttons: ImgBtn, TxtBtn implemented as function objects. They share a similiar interface so the event handlers can call SetActive, for example, on a button=20 object without needing to know exactly=20 what type of button it is. **********************************************/ //---------------------------------- function ImgBtn( oId,bId,w,action ) //---------------------------------- { var t=3Dthis t.Perform =3D _IBP t.SetActive =3D _IBSetA t.SetInactive=3D _IBSetI t.SetPressed =3D _IBSetP t.SetDisabled=3D _IBSetD t.Enabled =3D _IBSetE t.ChangeIcon =3D null t.UserAction =3D action t.ChgState =3D _IBUI t.mObjId =3D oId t.mBorderId=3D bId t.mWidth =3D w t.mIsOn =3D t.mCurState =3D 0 } function _IBSetA() { if( this.mIsOn ) { obj=3Dthis.ChgState( gHiliteClr,gShadowClr,2 ) obj.style.posTop=3D0 } } function _IBSetI() { if( this.mIsOn ) { obj=3Dthis.ChgState( gFaceClr,gFaceClr,1 ) obj.style.posTop=3D0=20 } } function _IBSetP() { if( this.mIsOn ) { obj=3Dthis.ChgState( gShadowClr,gHiliteClr,2 ) obj.style.posLeft+=3D1; obj.style.posTop+=3D1 } } function _IBSetD() { =20 obj=3Dthis.ChgState( gFaceClr,gFaceClr,0 ) obj.style.posTop=3D0=20 } function _IBSetE( state ) { var t=3Dthis GetObj( t.mBorderId ).style.visibility=3D"visible" if( state !=3D t.mIsOn ) { t.mIsOn=3Dstate if( state ) t.SetInactive() else t.SetDisabled() } } function _IBP() { var t=3Dthis if( t.mIsOn ) { if( t.UserAction !=3D null ) t.UserAction() if( t.ChangeIcon ) { obj=3DGetObj(t.mObjId) if( t.ChangeIcon() ) obj.style.posLeft=3Dobj.style.posLeft+(t.mCurState-4)*t.mWidth else obj.style.posLeft=3Dobj.style.posLeft+(t.mCurState-0)*t.mWidth } t.SetActive() } =20 } function _IBUI( clr1,clr2,nextState ) { var t=3Dthis SetBorder( GetObj( t.mBorderId ),clr1,clr2 ) obj=3DGetObj( t.mObjId ) obj.style.posLeft=3Dobj.style.posLeft+(t.mCurState-nextState)*t.mWidth-obj= .style.posTop t.mCurState=3DnextState return obj } //----------------------------------------- function TxtBtn( oId,oeId,action,chkState ) //----------------------------------------- { var t=3Dthis t.Perform =3D _TBP t.SetActive =3D _TBSetA t.SetInactive=3D _TBSetI t.SetPressed =3D _TBSetP t.SetDisabled=3D _TBSetD t.SetEnabled =3D _TBSetE t.GetState =3D chkState t.UserAction =3D action t.ChgState =3D _TBUI t.mObjId =3D oId t.m_elementsId=3D oeId t.mIsOn =3D 1 } function _TBSetA() { var t=3Dthis if( t.mIsOn && !t.GetState() ) t.ChgState( gHiliteClr,gShadowClr,0,0 ) } function _TBSetI() { var t=3Dthis if( t.mIsOn && !t.GetState() ) t.ChgState( gFaceClr,gFaceClr,0,0 ) } function _TBSetP() { if( this.mIsOn ) this.ChgState( gShadowClr,gHiliteClr,1,1 ) } function _TBSetD() { =20 this.ChgState( gFaceClr,gFaceClr,0,0 ) this.mIsOn =3D 0 } function _TBSetE() { var t=3Dthis if( !t.GetState() ) t.ChgState( gFaceClr,gFaceClr,0,0 ) else t.ChgState( gShadowClr,gHiliteClr,1,1 ) t.mIsOn =3D 1 } function _TBP() { var t=3Dthis if( t.mIsOn ) {=20 if( t.UserAction !=3D null ) t.UserAction() if( !t.GetState ) return if( t.GetState() ) t.SetPressed() else t.SetActive() } =20 } function _TBUI( clr1,clr2,lOffset,tOffset ) { SetBorder( GetObj( this.mObjId ),clr1,clr2 ) Offset( GetObj( this.m_elementsId ),lOffset,tOffset ) } function Offset( obj, top, left ){ obj.style.top=3Dtop; obj.style.left=3Dle= ft } function SetBorder( obj, upperLeft, lowerRight ) { s=3Dobj.style; s.borderStyle =3D "solid" s.borderWidth =3D 1=20 s.borderLeftColor =3D s.borderTopColor =3D upperLeft s.borderBottomColor=3D s.borderRightColor =3D lowerRight } function GetBtnObj(){ return gBtnArr[window.event.srcElement.id] } function BtnOnOver(){ b=3DGetBtnObj(); if( b !=3D null ) b.SetActive() } function BtnOnDown(){ b=3DGetBtnObj(); if( b !=3D null ) b.SetPressed() } function BtnOnOut(){ b=3DGetBtnObj(); if( b !=3D null ) b.SetInactive() } function BtnOnUp() { b=3DGetBtnObj() if( b !=3D null ) b.Perform() else Upd() } function GetNtsState(){ return parent.gNtsOpen } function GetOtlState(){ return parent.gOtlOpen } function GetOtlTxtState(){ return parent.gOtlTxtExp } function NtsBtnSetFlag( fVal ) { s=3Ddocument.all.item( this.m_flagId ).style s.display=3D"none" if( fVal ) s.display=3D"" else s.display=3D"none" } function _BSetA_Border(){ b =3D gBtnArr[this.mObjId]; if( b !=3D null ) b.S= etActive() } function _BSetI_Border(){ b =3D gBtnArr[this.mObjId]; if( b !=3D null ) b.S= etInactive() } function _BSetP_Border(){ b =3D gBtnArr[this.mObjId]; if( b !=3D null ) b.S= etPressed() } function _BSetA_BorderImg() {=20 b =3D gBtnArr[this.mBorderId]=20 if( b !=3D null && this.mIsOn && !b.GetState() ) { obj=3Dthis.ChgState( gHiliteClr,gShadowClr,2 ) obj.style.posTop=3D0 } } function _BSetI_BorderImg() {=20 b =3D gBtnArr[this.mBorderId] if( b !=3D null && this.mIsOn && !b.GetState() ) { obj=3Dthis.ChgState( gFaceClr,gFaceClr,1 ) obj.style.posTop=3D0 } } var gHiliteClr=3D"THREEDHIGHLIGHT",gShadowClr=3D"THREEDSHADOW",gFaceClr=3D"= THREEDFACE" var gBtnArr =3D new Array() gBtnArr["nb_otl"] =3D new TxtBtn( "nb_otl","nb_otlElem",parent.ToggleOtlPan= e,GetOtlState ) gBtnArr["nb_otlElem"] =3D new TxtBtn( "nb_otl","nb_otlElem",parent.ToggleOt= lPane,GetOtlState ) gBtnArr["nb_nts"] =3D new ImgBtn( "nb_nts","nb_ntsBorder",10,parent.ToggleN= tsPane ) gBtnArr["nb_nts"].SetActive =3D _BSetA_BorderImg; gBtnArr["nb_nts"].SetInactive =3D _BSetI_BorderImg; gBtnArr["nb_ntsBorder"] =3D new TxtBtn( "nb_ntsBorder","nb_ntsElem",parent.= ToggleNtsPane,GetNtsState ) gBtnArr["nb_ntsElem"] =3D new TxtBtn( "nb_ntsBorder","nb_ntsElem",parent.To= ggleNtsPane,GetNtsState ) gBtnArr["nb_prevBorder"] =3D gBtnArr["nb_prev"]=3D new ImgBtn( "nb_prev","n= b_prevBorder",30,parent.GoToPrevSld ) gBtnArr["nb_nextBorder"] =3D gBtnArr["nb_next"]=3D new ImgBtn( "nb_next","n= b_nextBorder",30,parent.GoToNextSld ) gBtnArr["nb_sldshw"]=3D new ImgBtn( "nb_sldshw","nb_sldshwBorder",18,parent= .FullScreen ) gBtnArr["nb_sldshwBorder"] =3D new TxtBtn( "nb_sldshw","nb_sldshwBorder",pa= rent.FullScreen,null ) gBtnArr["nb_sldshwBorder"].SetActive =3D _BSetA_Border; gBtnArr["nb_sldshwBorder"].SetInactive =3D _BSetI_Border; gBtnArr["nb_sldshwText"] =3D new TxtBtn( "nb_sldshw","nb_sldshwText",parent= .FullScreen,null ) gBtnArr["nb_sldshwText"].SetActive =3D _BSetA_Border; gBtnArr["nb_sldshwText"].SetInactive =3D _BSetI_Border; gBtnArr["nb_voice"] =3D gBtnArr["nb_voiceBorder"] =3D new ImgBtn( "nb_voice= ","nb_voiceBorder",18,parent.ToggleVNarration ) gBtnArr["nb_otlTxtBorder"] =3D gBtnArr["nb_otlTxt"]=3D new ImgBtn( "nb_otlT= xt","nb_otlTxtBorder",23,parent.ToggleOtlText ) gBtnArr["nb_ntsBorder"].m_flagId=3D "nb_nts" gBtnArr["nb_ntsBorder"].SetFlag =3D NtsBtnSetFlag gBtnArr["nb_otlTxt"].ChangeIcon=3D GetOtlTxtState /********************************************* Context menu implementation _CM() is the function that's hooked up to the oncontextmenu event. Once we're asked to show the menu, we first build it by creating DIVs on-the-fly. Then we position it=20 within the screen area so it doesn't get clipped. Creating the DIVs using createElement() means we don't have to write out any extra HTML into the slide HTML files. **********************************************/ var sNext=3D"Next",sPrev=3D"Previous",sEnd=3D"End Show",sFont=3D"Arial",sAr= row=3D"Arrow",sFreeform=3D"Freeform",sRect=3D"Rectangle",sOval=3D"Oval" function ShowMenu() { BuildMenu(); var doc=3DPPTSld.document.body,x=3DPPTSld.event.clientX+doc.scrollLeft,y= =3DPPTSld.event.clientY+doc.scrollTop m =3D PPTSld.document.all.item("ctxtmenu") m.style.pixelLeft=3Dx if( (x+m.scrollWidth > doc.clientWidth)&&(x-m.scrollWidth > 0) ) m.style.pixelLeft=3Dx-m.scrollWidth m.style.pixelTop=3Dy if( (y+m.scrollHeight > doc.clientHeight)&&(y-m.scrollHeight > 0) ) m.style.pixelTop=3Dy-m.scrollHeight m.style.display=3D"" } function _CM() { if( !parent.IsFullScrMode() ) return; if(!PPTSld.event.ctrlKey) { ShowMenu() return false } else HideMenu() } function BuildMenu() { if( PPTSld.document.all.item("ctxtmenu") ) return var mObj=3DCreateItem( PPTSld.document.body ) mObj.id=3D"ctxtmenu" mObj.style.visibility=3D"hidden" var s=3DmObj.style s.position=3D"absolute" s.cursor=3D"default" s.width=3D"120px" SetCMBorder(mObj,"menu","black") var iObj=3DCreateItem( mObj ) SetCMBorder( iObj, "threedhighlight","threedshadow" ) iObj.style.padding=3D2 CreateMenuItem( iObj,sNext,M_GoNextSld,M_True ) CreateMenuItem( iObj,sPrev,M_GoPrevSld,M_HasPrevSld ) =09 CreateSeparator( iObj ) CreateMenuItem( iObj,sEnd,M_End,M_True ) mObj.style.visibility=3D"visible" } function Cancel() { window.event.cancelBubble=3Dtrue; window.event.returnVa= lue=3Dfalse } function Highlight() { ChangeClr("activecaption","threedhighlight") } function Deselect() { ChangeClr("threedface","menutext") } function Perform() { e=3DPPTSld.event.srcElement if( e.type=3D=3D"menuitem" && e.IsActive() ) e.Action() else PPTSld.event.cancelBubble=3Dtrue } function ChangeClr( bg,clr ) { e=3DPPTSld.event.srcElement if( e.type=3D=3D"menuitem" && e.IsActive() ) { e.style.backgroundColor=3Dbg e.style.color=3Dclr } } function M_HasPrevSld() { return( parent.HasPrevSld() ) } function M_GoNextSld() { if( gIsEndShow ) M_End(); else GoToNextSld() } function M_GoPrevSld() { if( gIsEndShow ) { gIsEndShow=3D0; history.back();= PPTSld.event.cancelBubble=3Dtrue; } else GoToPrevSld() } function M_True() { return true } function M_End() { window.close( self ) } function CreateMenuItem( node,text,action,eval ) { var e=3DCreateItem( node ) e.type=3D"menuitem" e.Action=3Daction e.IsActive=3Deval e.innerHTML=3Dtext if( !e.IsActive() ) e.style.color=3D"threedshadow" e.onclick=3DPerform e.onmouseover=3DHighlight e.onmouseout=3DDeselect s=3De.style; 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charset="us-ascii" Translingual Topic Tracking with PRISE ------=_NextPart_01C82FBF.787DABA0 Content-Location: file:///C:/B278E252/796f0712_files/outline.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii"
 No= tes
Slide Show
Outline
= = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
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Document-Language IR
<= b>Retrieval
<= b> Engine
Translation System
Chinese =
queries
Chinese =
documents
Results<= /b>
English
queries
select
examine<= /i>
Chinese Document
Collection