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Information in the Digital Environment Information Seeking Models Dr. Dania Bilal IS 530 Spring 2005

Information in the Digital Environment Information Seeking Models

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Information in the Digital Environment Information Seeking Models. Dr. Dania Bilal IS 530 Spring 2005. Information Options. Print CD-ROM databases Remote databases (e.g., Dialog) Web. Print Option. Inexpensive Owned by library Easily accessible. CD-ROM Databases. Purchase or lease - PowerPoint PPT Presentation

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Page 1: Information in the Digital Environment Information Seeking Models

Information in the Digital EnvironmentInformation Seeking Models

Dr. Dania BilalIS 530Spring 2005

Page 2: Information in the Digital Environment Information Seeking Models

Information Options

Print CD-ROM databases Remote databases (e.g., Dialog) Web

Page 3: Information in the Digital Environment Information Seeking Models

Print Option

Inexpensive Owned by library Easily accessible

Page 4: Information in the Digital Environment Information Seeking Models

CD-ROM Databases

Purchase or lease Subscription Library responsible for software &

hardware Most common is CD-ROM

Page 5: Information in the Digital Environment Information Seeking Models

CD-ROM

High storage (650 mg to over a gigabyte) 650 mg equivalent to 250,000 pages of

text or 1 million catalog records Can be loaded on stand-alone or

networked computers. Site license is needed

Page 6: Information in the Digital Environment Information Seeking Models

Remote Databases

Known as commercial databases Up-to-date Access to >100s of databases Low up-front cost Cost per search varies with database

used Requires expertise in searching

Page 7: Information in the Digital Environment Information Seeking Models

Web Information

Global access to information Low up-front cost Requires an ISP GUI interface Hypertext Access to full text information

Page 8: Information in the Digital Environment Information Seeking Models

Information Retrieval System (IR)

A set of components that interact to provide feedback

Comprised of interlinked entities Agency that creates the databases People Documents

Page 9: Information in the Digital Environment Information Seeking Models

Interlinked Entities

Agency

Documents

People

Page 10: Information in the Digital Environment Information Seeking Models

IR Information Transfer

Inputs Processes Objectives of the system Outputs

Page 11: Information in the Digital Environment Information Seeking Models

The IR Cycle

Page 12: Information in the Digital Environment Information Seeking Models

The IR Cycle

Documents are analyzed, translated, indexed, and stored.

Documents are organized Cataloging (description/representation of

docs.) Subject indexing

Page 13: Information in the Digital Environment Information Seeking Models

The IR Cycle

Subject indexinga) Determination of subject content

(conceptual analysis)b) Translation of content into language of

the system (controlled vocabulary)c) Abstracting

Page 14: Information in the Digital Environment Information Seeking Models

The IR Cycle

Language of the system (controlled vocabulary) List of subject headings (Pre-coordinate) Thesauri (Pre-coordinate) Classification scheme

Page 15: Information in the Digital Environment Information Seeking Models

The IR Cycle

Documents are represented by other entities Author(s) Date of publication Language Identifiers

Page 16: Information in the Digital Environment Information Seeking Models

The IR Cycle

Entities may become access points Documents are stored after indexing Document representation is entered

into the matching mechanism

Page 17: Information in the Digital Environment Information Seeking Models

The IR Cycle

A file of document surrogates is established

File becomes available for searching using a variety of access points

Page 18: Information in the Digital Environment Information Seeking Models

The IR Cycle

User Query Analyzed for conceptual content Translated into the language of the

system (matched against controlled vocabulary and keywords)

Matched against document surrogates in the database

Page 19: Information in the Digital Environment Information Seeking Models

Explanation of the IR Cycle

Output A set of records found and deemed

relevant to a user query User judgment of retrieval

Page 20: Information in the Digital Environment Information Seeking Models

User Judgment

Relevance to information need Relevance ranking by IR system Relevance vs. pertinence

Page 21: Information in the Digital Environment Information Seeking Models

Document-Based IRs

Input, output, and matching mechanisms

Selection of documents (done by indexers)

Analysis of documents (done by indexers)

Page 22: Information in the Digital Environment Information Seeking Models

Document-Based IRs

Document representation (done by indexers)

Analysis of user query (done by system)

Matching user query with relevant documents (done by system)

Delivery of documents (output)

Page 23: Information in the Digital Environment Information Seeking Models

Information Seeking

Page 24: Information in the Digital Environment Information Seeking Models

Information Seeking

Process of finding information to fill a knowledge gap

User requests Known item searches Unknown item searches Subject

searches

Page 25: Information in the Digital Environment Information Seeking Models

Information Seeking Models Ellis’ Behavioral Model Kuhlthau’s Information Search Process

Model Nahl’s ACS Model Marchionini’s Information Process Model Wilson’s Problem-Solving Model Belkin’s Information Seeking Strategies

(ISS) Belkin’s Anomalous State of Knowledge

(ASK)

Page 26: Information in the Digital Environment Information Seeking Models

Ellis’ Behavioral Model

Describes 8 information seeking patterns of social scientists, physical scientists, and engineers in using hypertext (e.g., the Web) Starting (Surveying), Chaining, Monitoring,

Browsing, Differentiating (Distinguishing), Filtering, Extracting, Verifying, Ending.

Page 27: Information in the Digital Environment Information Seeking Models

Kuhlthau’s ISP Model

Information search process from the user’s perspective in traditional environment

Affective, cognitive, and sensorimotor Six stages:

Initiation, Selection, Exploration, Formulation, Collection, Presentation

Page 28: Information in the Digital Environment Information Seeking Models

Nahl’s ACS Model

Taxonomic approach for identifying the levels of information seeking behaviors

Searcher’s feeling (A), thinking (C), and see or do (S) is termed “information behavior”

Levels are sequential and continuous

Page 29: Information in the Digital Environment Information Seeking Models

Marchionini’s Model

Problem solving approach to understanding information seeking process in the electronic environment

Eight processes: Problem recognition, Problem definition,

Selection of system/source, Problem articulation (query formulation), Search execution, Examination of results, Extraction of desired information; Reflection, Iteration, and Stopping of search process

Page 30: Information in the Digital Environment Information Seeking Models

Wilson’s Problem-Solving Model

Goal-directed behavior of problem solving that advances from uncertainty to certainty through the stages of the problem-resolution process: Problem identification, Problem

definition, Problem resolution, Solution statement (has affective dimensions)

Stages are sequential and non-linear

Page 31: Information in the Digital Environment Information Seeking Models

Belkin’s ISS Model

Task-oriented with 4 sets of tasks: Browsing: scanning or searching a resource Learning: expanding knowledge of goal,

problem, & system used Recognition: identifying relevant items Meta information: interaction with items that

map the boundaries of the task

Dynamic process

Page 32: Information in the Digital Environment Information Seeking Models

Belkin’s ASK Theory

ASK (Anomalous State of Knowledge) “The cognitive and situational aspects that were the reason for seeking information and approaching an IR system” (Saracevic, 1996).

Knowledge gap (anomaly) and the need to solve it

Implications for system design