Structure of IR Systems
LBSC 796/INFM 718R
Session 1, September 10, 2007
Doug Oard
Agenda
•	Teaching theater orientation

•	The structure of interactive IR systems

•	Course overview
What is IR?
•	Information retrieval is a problem-oriented discipline, concerned with the problem of the effective and efficient transfer of desired information between human generator and human user
Information Retrieval Systems
•	Information
–	What is “information”?
•	Retrieval
–	What do we mean by “retrieval”?
–	What are different types information needs?
•	Systems
–	How do computer systems fit into the human information seeking process?
Information Hierarchy
Information Hierarchy
•	Data
–	The raw material of information
•	Information
–	Data organized and presented in a particular manner
•	Knowledge
–	“Justified true belief”
–	Information that can be acted upon
•	Wisdom
–	Distilled and integrated knowledge
–	Demonstrative of high-level “understanding”
What do We Mean by “Information?”
•	How is it different from “data”?
–	Information is data in context
•	Databases contain data and produce information
•	IR systems contain and provide information

•	How is it different from “knowledge”?
–	Knowledge is a basis for making decisions
•	Many “knowledge bases” contain decision rules
A (Facetious) Example
•	Data
–	98.6º F, 99.5º F, 100.3º F, 101º F, …
•	Information
–	Hourly body temperature: 98.6º F, 99.5º F, 100.3º F, 101º F, …
•	Knowledge
–	If you have a temperature above 100º F, you most likely have a fever
•	Wisdom
–	If you don’t feel well, go see a doctor
What types of information?
•	Text
•	Structured documents (e.g., XML)
•	Images
•	Audio (sound effects, songs, etc.) 
•	Video
•	Programs
•	Services

What Do We Mean by “Retrieval?”
•	Find something that you want
–	The information need may or may not be explicit

•	Known item search
–	Find the class home page

•	Answer seeking
–	Is Lexington or Louisville the capital of Kentucky?

•	Directed exploration
–	Who makes videoconferencing systems?
Relevance
•	Relevance relates a topic and a document
–	Duplicates are equally relevant, by definition
–	Constant over time and across users

•	Pertinence relates a task and a document
–	Accounts for quality, complexity, language, …

•	Utility relates a user and a document
–	Accounts for prior knowledge
Systems: The Memex
What Do People Search For?
•	Searchers often don’t clearly understand
–	The problem they are trying to solve
–	What information is needed to solve the problem
–	How to ask for that information

•	The query results from a clarification process

•	Dervin’s “sense making”: 

Types of Information Needs
•	Retrospective (“Retrieval”)
–	“Searching the past”
–	Different queries posed against a static collection
–	Time invariant
•	Prospective (“Filtering”)
–	“Searching the future”
–	Static query posed against a dynamic collection
–	Time dependent
Design Strategies
•	Foster human-machine synergy
–	Exploit complementary strengths
–	Accommodate shared weaknesses

•	Divide-and-conquer 
–	Divide task into stages with well-defined interfaces
–	Continue dividing until problems are easily solved

•	Co-design related components
–	Iterative process of joint optimization
Divide and Conquer
•	Strategy: use encapsulation to limit complexity
•	Approach:
–	Define interfaces (input and output) for each component
–	Define the functions performed by each component
–	Study each component in isolation
–	Repeat the process within components as needed
–	Make sure that this decomposition makes sense
•	Result: a hierarchical decomposition
Process/System Co-Design
Human-Machine Synergy
•	Machines are good at:
–	Doing simple things accurately and quickly
–	Scaling to larger collections in sublinear time

•	People are better at:
–	Accurately recognizing what they are looking for
–	Evaluating intangibles such as “quality”

•	Both are pretty bad at:
–	Mapping consistently between words and concepts
Supporting the Search Process
Supporting the Search Process
Where to Start?
•	Study the IR black box in isolation
–	Simple behavior: in goes query, out comes documents
–	Optimize the choice of documents that come out

The IR Black Box
Inside The IR Black Box
Search Component Model
What about databases?
•	What are examples of databases?
–	Banks storing account information
–	Retailers storing inventories
–	Universities storing student grades
•	What exactly is a (relational) database?
–	Think of them as a collection of tables
–	They model some aspect of “the world”
A (Simple) Database Example
Database Queries
•	What would you want to know from a database?
–	What classes is John Arrow enrolled in?
–	Who has the highest grade in LBSC 690?
–	Who’s in the history department?
–	Of all the non-CLIS students taking LBSC 690 with a last name shorter than six characters and were born on a Monday, who has the longest email address?

Databases vs. IR
“Bag of Terms” Representation
•	Bag = a “set” that can contain duplicates
•	“The quick brown fox jumped over the lazy dog’s back” 
   		{back, brown, dog, fox, jump, lazy, over, quick, the, the}

•	Vector = values recorded in any consistent order
•	{back, brown, dog, fox, jump, lazy, over, quick, the, the} 
	[1 1 1 1 1 1 1 1 2]
Bag of Terms Example
Advantages of Ranked Retrieval
•	Closer to the way people think
–	Some documents are better than others

•	Enriches browsing behavior
–	Decide how far down the list to go as you read it

•	Allows more flexible queries
–	Long and short queries can produce useful results
Counting Terms
•	Terms tell us about documents
–	If “rabbit” appears a lot, it may be about rabbits
•	Documents tell us about terms
–	“the” is in every document -- not discriminating
•	Documents are most likely described well by rare terms that occur in them frequently
–	Higher “term frequency” is stronger evidence
–	Low “document frequency” makes it stronger still
Document Length Normalization
•	Long documents have an unfair advantage
–	They use a lot of terms
•	So they get more matches than short documents
–	And they use the same words repeatedly
•	So they have much higher term frequencies

•	Normalization seeks to remove these effects
Problems with “Free Text” Search
•	Homonymy
–	Terms may have many unrelated meanings
–	Polysemy (related meanings) is less of a problem

•	Synonymy
–	Many ways of saying (nearly) the same thing

•	Anaphora
–	Alternate ways of referring to the same thing
Two Ways of Searching
Problems with Controlled Vocabulary
•	New concepts

•	Users and indexers may think differently

•	Using thesauri effectively requires training

Some Examples
Estimating Authority from Links
Problems with Observed Behavior
•	Protecting privacy
–	What absolute assurances can we provide?
–	How can we make remaining risks understood?

•	Scalable rating servers
–	Is a fully distributed architecture practical?

•	Non-cooperative users
–	How can the effect of spamming be limited?
Putting It All Together
The Big Picture
•	Four Factors, working together
–	User
–	Process
–	System
–	Collection
Course Goals
•	Appreciate IR system capabilities and limitations

•	Understand IR system design & implementation
–	For a broad range of applications and media

•	Evaluate IR system performance

•	Identify current IR research problems
Course Design
•	Text/readings provide background and detail
–	At least one recommended reading is required

•	Class provides organization and direction
–	We will not cover every important detail

•	Assignments and project provide experience
–	The TA can help with the project

•	Final exam helps focus your effort 
Assumed Background
•	Everyone:
–	LBSC 690 or INFM 603 or equivalent
–	Comfortable with learning about technology 
•	MIM Students:
–	Basic systems analysis, scripting languages
–	Some programming is helpful
•	MLS students:
–	LBSC 650 and LBSC 670
–	LBSC 750 or a subject access course is helpful 
Grading
•	Assignments (20%)
–	Mastery of concepts and experience using tools

•	Term project (50%)
–	Options are described on course Web page

•	Final exam (30%)
–	In-class exam
Handy Things to Know
•	Classes will be videotaped
–	Available outside my office
•	Office hours: 5 PM Mondays
–	Or schedule by email, or ask after class
•	Everything is on the Web
–	At http://www.glue.umd.edu/~oard
•	Doug is most easily reached by email
–	oard@umd.edu
Some Things to Do This Week
•	Assignment 1
–	Due at 6 PM next Monday!!

•	At least skim the readings before class
–	Don’t fall behind!

•	Explore the Web site
–	Start thinking about the term project