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Language Models
LBSC 796/CMSC 828o
Session 4, February 16, 2004
Douglas W. Oard
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•<= /span>Questions
•
•<= /span>The meaning of “maybe”
•
•<= /span>Probabilistic retrieval
•
•Comparison with vector space model<= /div>
Agenda
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Muddiest Points
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•Why disti= nguish utility and relevance?
<= span class=3DBB style=3D'position:absolute;left:-3.82%'>•How coord= ination measure is ranked Boolean
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•Why use t= erm weights?
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•The meani= ng of DF
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•The probl= em with log(1)=3D0
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•How the v= ectors are built
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•How to do= cosine normalization (5)
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•Why to do= cosine normalization (2)
<= span class=3DBB style=3D'position:absolute;left:-4.39%'>•Okapi gra= phs
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Supporting the Search Process
Source
Selection
Search
Query
Selection
Ranked List
Examination
Document
Delivery
Document
Query
Formulation
IR System
Indexing
Index
Acquisition
Collection
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{
{
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Looking Ahead
&#= 8226;We ask “is this document relevant?”
&= #8211;Vector space: we answer “somewhat”
&= #8211;Probabilistic: we answer “probably”
– <= /div>
&#= 8226;The key is to know what “probably” means
&= #8211;First, we’ll formalize that notion
&= #8211;Then we’ll apply it to retrieval
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Probability
&#= 8226;What is probability?
&= #8211;Statistical: relative frequency as n ® ¥
&= #8211;Subjective: degree of belief
• <= /div>
&#= 8226;Thinking statistically
&= #8211;Imagine a finite amount of “stuff”
&= #8211;Associate the number 1 with the total amount
&= #8211;Distribute that “mass” over the possible events
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Statistical Independence
<= span class=3DBB style=3D'position:absolute;left:-4.47%'>•A and B a= re independent if and only if:
–    P(A and B) =3D P(A) <= span style=3D'font-family:Symbol;mso-char-type:symbol'>´ P(B) =
–
•Independen= ce formalizes “unrelated”
<= span class=3DB1B style=3D'position:absolute;left:-4.23%'>–P(“= ;being brown eyed”) =3D 85/100
<= span class=3DB1B style=3D'position:absolute;left:-4.23%'>–P(“= ;being a doctor”) =3D 1/1000
<= span class=3DB1B style=3D'position:absolute;left:-3.7%'>–P(“= being a brown eyed doctor”) =3D 85/100,000
R= 11;
= 226;
Think of it this way.  Out of 100,000 people, you expect a thousandth to be doctors -- that’s 100 people.=
Out of those 100 people, you expect 85 to have brown eyes.  So you expect 85 of the original 100,000 to be brown-eyed doctors.
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Dependent Events
<= span class=3DBB style=3D'position:absolute;left:-4.31%'>•Suppose&#= 8221;
<= span class=3DB1B style=3D'position:absolute;left:-3.85%'>–P(“= ;having a B.S. degree”) =3D 2/10
<= span class=3DB1B style=3D'position:absolute;left:-3.85%'>–P(“= ;being a doctor”) =3D 1/1000
<= span class=3DBB style=3D'position:absolute;left:-4.31%'>•Would you expect
<= span class=3DB1B style=3D'position:absolute;left:-3.76%'>–P(“= ;having a B.S. degree and being a doctor”)
–    =3D 2/10,000   ???
<= span class=3DBB style=3D'position:absolute;left:-4.31%'>•Extreme example:
<= span class=3DB1B style=3D'position:absolute;left:-3.85%'>–P(“= ;being a doctor”) =3D 1/1000
<= span class=3DB1B style=3D'position:absolute;left:-3.85%'>–P(“= ;having studied anatomy”) =3D 12/1000
You know 10/1000 are doctors, and more than your average number of them (2 out of = 10) are likely to have a B.S. degree.  If you assume they’re independent, the probability you get is very much an underestimate of the true probability.
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Conditional Probability
•P(A | B)<= span style=3D'mso-spacerun:yes'>  º  = P(A and B) / P(B)
A
B
A an= d B
•<= /span> P(A= ) =3D prob of A relative to the whole space
• P(A= |B) =3D prob of A considering only the       <= span style=3D'font-size:133%'>         = ; cases where B is known to be true
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More on Conditional Probability
<= span class=3DBB style=3D'position:absolute;left:-3.86%'>•Suppose&#= 13;
<= span class=3DB1B style=3D'position:absolute;left:-3.44%'>–P(“= ;having studied anatomy”) =3D 12/1000
<= span class=3DB1B style=3D'position:absolute;left:-2.94%'>–P(“= ;being a doctor and having studied anatomy”) =3D 1/1000
<= span class=3DBB style=3D'position:absolute;left:-3.86%'>•Consider&= #13;
<= span class=3DB1B style=3D'position:absolute;left:-3.12%'>–P(“= ;being a doctor” | “having studied anatomy”) =3D 1/12 =
<= span class=3DBB style=3D'position:absolute;left:-3.38%'>•But if yo= u assume all doctors have studied anatomy
<= span class=3DB1B style=3D'position:absolute;left:-3.32%'>–P(“= ;having studied anatomy” | “being a doctor”) =3D 1
Useful restatemen= t of definition:  P(A and B) =3D P= (A|B) x P(B)
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Some Notation
•Consider <= /div>
–A set of hypotheses:    H1, H2, H3 =
–Some observable eviden= ce    O
•<= /span>
•P(O|H1) =3D probabilit= y of O being observed
• =    if we knew H1 were true
•P(O|H2) =3D probabilit= y of O being observed
• =    if we knew H2 were true
•P(O|H3) =3D probabilit= y of O being observed
• =    if we knew H3 were t= rue
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An Example
•L= et
–O = =3D “Joe earns more than $80,000/year”
–H1= =3D “Joe is a doctor”
–H2= =3D “Joe is a college professor”
–H3= =3D “Joe works in food services”
•S= uppose we do a survey and we find out
–P(= O|H1) =3D 0.6
–P(= O|H2) =3D 0.07
–P(= O|H3) =3D 0.001
•W= hat should be our guess about Joe’s profession?
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Bayes’ Rule
= 226;What’s P(H1|O)?  P(H2|O)?  P(H3|O)?
&#= 8226;Theorem:
R= 11;
P(H | O)   =3D 
P(O | = H) x  P(H)
        P(O)
Posterior
probability
Prior
probability
•<= /span>Notice that the prior is very important!
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Back to the Example
&#= 8226;Suppose we also have good data about priors:
&= #8211;P(O|H1) =3D 0.6 P(H1) =3D 0.000= 1  docto= r
&= #8211;P(O|H2) =3D 0.07 P(H2) =3D 0.001=     pro= f
&= #8211;P(O|H3) =3D 0.001 P(H3) =3D 0.2=         food
&#= 8226;We can calculate
&= #8211;P(H1|O) =3D  0.00006 / P(“earning > $70K/year”)
&= #8211;P(H2|O) =3D  0.0007 / P(“earning > $70K/year”)
&= #8211;P(H3|O) =3D  0.0002 / P(“earning > $70K/year”)
Notice that in this example, the prior probabilities reflect the likelihood of someone having a particular kind of job, ignoring any information about income.  E.g. we’= ;re supposing food services workers are estimated at 20% of the population.  Thus the best guess about profes= sion prior to info about income would be food services worker.
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Key Ideas
&#= 8226;Defining probability using frequency
–
&#= 8226;Statistical independence
–
&#= 8226;Conditional probability
–
&#= 8226;Bayes’ rule
•
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•<= /span>Questions
•
•<= /span>Defining probability
• = ;
•Using probability for retrieval =
–Language modeling
–Inference networks
–
•Comparison with vector space model<= /div>
Agenda
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Probability Ranking Principle
&#= 8226;Assume binary relevance/document independence
&#= 8211;Each document is either relevant or it is not
&= #8211;Relevance of one doc reveals nothing about another
– <= /div>
&#= 8226;Assume the searcher works down a ranked list
&#= 8211;Seeking some number of relevant documents
– <= /div>
&#= 8226;Theorem (provable from assumptions):
–Documents should be ranked in order of decreasing probability of relevance to the query,
R= 11; P(d relevant-to q)
Notion of “partly relevant” in vector space models has been replaced= by yes-or-no -- document d is relevant or it’s not.  The focus is then on the probabi= lity of the event “document d is in fact relevant to query q”.
Question: what are some counter-examples that show the assumptions are too strong?<= /font>
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Probabilistic Retrieval Strategy
<= span class=3DBB style=3D'position:absolute;left:-4.03%'>•Estimate = how terms contribute to relevance
<= span class=3DB1B style=3D'position:absolute;left:-3.85%'>–How do T= F, DF, and length influence your judgments about document relevance?  (e.g., Okapi) = ;
= 226;
<= span class=3DBB style=3D'position:absolute;left:-3.59%'>•Combine t= o find document relevance probability
= 226;
<= span class=3DBB style=3D'position:absolute;left:-4.04%'>•Order doc= uments by decreasing probability
In addition to the “document independence assumption” on previous slide, we have a “term independence assumption”: terms’ contributions to relevance are treated as independent events.
Okapi is one particular way of estimating probability given tf, df, and length.
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Where do the probabilities fit?
Comparison Function
Representation Function
Query Formulation
Human Judgment
Representation Function<= /div>
Retrieval Status Value
Utility
Query=
Information Need
Docum= ent
Query Representation
Document Representation
3D"Text=
Query  Processing
3D"Text
Document  Processing
P(d is Rel | q)
Start 1:20
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Binary Independence Model
•Binary refers again to binary relevance
•<= /span>
•Assume “te= rm independence”
–Presence of one term t= ells nothing about another
•<= /span>
•Assume “uniform priors”
–P(d) is the same for a= ll d
“Binary”: relevance is yes-or-no.  “Independence”: term contributions are independent.
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“Okapi” Term Weights =
TF component
IDF component
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Stochastic Language Models
•Models probability of generating= any string
0.2 the
0.1 a
0.01 = man
0.01 = woman
0.03 = said
0.02 = likes
…
the
man
likes
the
woman
0.2
0.01
0.02
0.2
0.01
multiply
Model M
P(s | M)
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Language Models, cont’d
•Models probability of generating= any string
0.2 the
0.1 a
0.01 man
0.01 woman
0.03 said
0.02 likes
…
Model M1
0.2 the
0.1 yon
0.001 class
0.01 maiden
0.03 sayst
0.02 pleaseth
…
Model M2<= /span>
maid= en
clas= s
plea= seth
yon<= /span>
the
0.0005
0.01
0.0001
0.0001
0.2
0.01
0.0001
0.02
0.1
0.2
P(s|M2)  >  P(s|M1)
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Retrieval with Language Models
&#= 8226;Treat each document as the basis for a model
– <= /div>
&#= 8226;Rank document d based on P(d | q)
&= #8211;P(d | q) =3D P(q | d)  x  P(d)  /  P(q)
&#= 8226;P(q) is same for all documents, can’t change ranks
&= #8226;P(d) [the prior] is often treated as the same for all d
&= #8211;But we could use criteria like authority, length, genre
&= #8226;P(q | d) is the probability of q given d’s model
&= #8211;Same as ranking by P(q | d)
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Computing P(q | d)
&#= 8226;Build a smoothed language model for d
&= #8211;Count the frequency of each term in d
&= #8211;Count the frequency of each term in the collection
&= #8211;Combine the two in some way
&= #8211;Redistribute probabilities to unobserved events
&= #8226;Example: add 1 to every count
» <= /div>
&#= 8226;Combine the probability for the full query
&= #8211;Summing over the terms in q is a soft “OR”
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Key Ideas
&#= 8226;Probabilistic methods formalize assumptions
&= #8211;Binary relevance
&= #8211;Document independence
&= #8211;Term independence
&= #8211;Uniform priors
&= #8211;Top-down scan
» <= /div>
&#= 8226;Natural framework for combining evidence
&= #8211;e.g., non-uniform priors
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Inference Networks
•<= /span>A flexible way of combining term weights
–<= /span>Boolean model
–<= /span>Binary independence model
–<= /span>Probabilistic models with weaker assumptions <= /span>
•= 3;
•<= /span>Key concept: rank based on P(d | q)
–P(d | q) =3D P(q | d)<= span style=3D'mso-spacerun:yes'>  x P(d)  /  P(q)
•
•<= /span>Efficient large-scale implementation
–<= /span>InQuery text retrieval system from U Mass
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A Boolean Inference Net
bat
d1
d2
d3
d4
cat
fat
hat
mat
pat
rat
vat
AND
OR
sat
AND
I
Information need
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A Binary Independence Network
bat
d1
d2
d3
d4
cat
fat
hat
mat
pat
rat
vat
sat
query
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Probability Computation
= 226;Turn on exactly one document at a time
&= #8211;Boolean:  Every connected term turns on = ;
&= #8211;Binary Ind:  Connected terms gain th= eir weight
&#= 8226;Compute the query value
&= #8211;Boolean:  AND and OR nodes use truth tables=
&= #8211;Binary Ind:  Fraction of the possible weight
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A Critique
&#= 8226;Most of the assumptions are not satisfied!
&= #8211;Searchers want utility, not relevance
&= #8211;Relevance is not binary
&= #8211;Terms are clearly not independent
&= #8211;Documents are often not independent
&#= 8226;The best known term weights are quite ad hoc
&= #8211;Unless some relevant documents are known
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But It Works!
•Ranked retrieval parad= igm is powerful
–Well suited to human search strategies
»
•Probability theory has explanatory power
–At least we know where= the weak spots are
–Probabilities are good= for combining evidence
»
•Good implementations e= xist (InQuery, Lemur)
–Effective, efficient, = and large-scale
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Comparison With Vector Space
&#= 8226;Similar in some ways
&= #8211;Term weights can be based on frequency
&= #8211;Terms often used as if they were independent
– <= /div>
&#= 8226;Different in others
&= #8211;Based on probability rather than similarity
&= #8211;Intuitions are probabilistic rather than geometric
–
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One Minute Paper
•<= /span>Which assumption underlying the probabilistic retrieval model causes you the most concern, and why?
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‹header›=
‹date/time›
Click to edit Master text styles
Second level
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‹footer›=
‹#›
Think of it this way.  Out of 100,000 people, you expect= a thousandth to be doctors -- that’s 100 people. Out of those 100 people, you expect 85 to have brown eyes.=   So you expect 85 of the original 100,000 to be brown-eyed doctors.<= /div>
You know 10/1000 are doctors, and= more than your average number of them (2 out of 10) are likely to have a B.S. degree.  If you assume they’re independent, the probability you get is very much an unde= restimate of the true probability.
Notice that in this example, the = prior probabilities reflect the likelihood of someone having a particular kind of job, ignoring any information about income.  E.g. we’re supposing food services workers are estimated at 20% of the population.  Thus the best guess about profess= ion prior to info about income would be food services worker.
Notion of “partly relevant&= #8221; in vector space models has been replaced by yes-or-no -- document d is relevant or it’s not.  = The focus is then on the probability of the event “document d is in fact relevant to query q”. Question: what are some counter-examples t= hat show the assumptions are too strong?
In addition to the “document independence assumption” on previous slide, we have a “term independence assumption”: terms’ contributions to relevance ar= e treated as independent events.
Okapi is one particular way of estimating probability given tf, df, a= nd length.
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“Binary”: relevance is yes-or-no.  “Independence”: term contributions are independent.
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} if( MakeNotesVis() ) return runAnimations =3D _InitAnimations(); =09 if( IsWin("PPTSld") ) parent.SldUpdated(GetSldId()) g_origSz=3DparseInt(SlideObj.style.fontSize) g_origH=3Dsld.style.posHeight g_origW=3Dsld.style.posWidth g_scaleHyperlinks=3D(document.all.tags("AREA").length>0) if( g_scaleHyperlinks ) InitHLinkArray() if( g_scaleInFrame||(IsWin("PPTSld") && parent.IsFullScrMode() ) ) document.body.scroll=3D"no" _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 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gSldJumpIdx =3D ""; win.GoToSld( parent.GetSldList().mList[jumpTo-1].mSldHref ) } } } function _KDH() { if( event.keyCode =3D=3D 8 ) { event.returnValue =3D 0; parent.GoToPrevSld(); } }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=3D34, 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("slide0034.htm",1,-1,1),new hrefList(= "slide0015.htm",1,-1,1),new hrefList("slide0032.htm",1,-1,1),new hrefList("= slide0036.htm",1,-1,1),new hrefList("slide0035.htm",1,-1,1),new hrefList("s= lide0002.htm",1,-1,1),new hrefList("slide0003.htm",1,-1,1),new hrefList("sl= ide0004.htm",1,-1,1),new hrefList("slide0005.htm",1,-1,1),new hrefList("sli= de0006.htm",1,-1,1),new hrefList("slide0007.htm",1,-1,1),new hrefList("slid= e0008.htm",1,-1,1),new hrefList("slide0009.htm",1,-1,1),new hrefList("slide= 0010.htm",1,-1,1),new hrefList("slide0011.htm",1,-1,1),new hrefList("slide0= 016.htm",1,-1,1),new hrefList("slide0017.htm",1,-1,1),new hrefList("slide00= 18.htm",1,-1,1),new hrefList("slide0027.htm",1,-1,1),new hrefList("slide001= 9.htm",1,-1,1),new hrefList("slide0037.htm",1,-1,1),new hrefList("slide0013= .htm",1,-1,1),new hrefList("slide0028.htm",1,-1,1),new hrefList("slide0029.= htm",1,-1,1),new hrefList("slide0038.htm",1,-1,1),new hrefList("slide0039.h= tm",1,-1,1),new hrefList("slide0020.htm",1,-1,1),new hrefList("slide0021.ht= m",1,-1,1),new hrefList("slide0022.htm",1,-1,1),new hrefList("slide0023.htm= ",1,-1,1),new hrefList("slide0024.htm",1,-1,1),new hrefList("slide0025.htm"= ,1,-1,1),new hrefList("slide0030.htm",1,-1,1),new hrefList("slide0031.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" PowerPoint Presentation ------=_NextPart_01C3F419.553D8240 Content-Location: file:///C:/B348D634/796s0404_files/outline.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii"
 No= tes
Slide Show
Outline
= = = = = = = = = = = = = = = = = = = = =
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