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 Subscription Library responsible for software & hardware Most common is CD-ROM
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
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
Web Information Global access to information Low up-front cost Requires an ISP GUI interface Hypertext Access to full text information
Information Retrieval System (IR) A set of components that interact to provide feedback Comprised of interlinked entities Agency that creates the databases People Documents
Interlinked Entities Agency Documents People
IR Information Transfer Inputs Processes Objectives of the system Outputs
The IR Cycle
Documents are analyzed, translated, indexed, and stored. Documents are organized Cataloging (description/representation of docs.) Subject indexing
The IR Cycle Subject indexing a) Determination of subject content (conceptual analysis) b) Translation of content into language of the system (controlled vocabulary) c) Abstracting
The IR Cycle Language of the system (controlled vocabulary) List of subject headings (Pre-coordinate) Thesauri (Pre-coordinate) Classification scheme
The IR Cycle Documents are represented by other entities Author(s) Date of publication Language Identifiers
The IR Cycle Entities may become access points Documents are stored after indexing Document representation is entered into the matching mechanism
The IR Cycle A file of document surrogates is established File becomes available for searching using a variety of access points
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
Explanation of the IR Cycle Output A set of records found and deemed relevant to a user query User judgment of retrieval
User Judgment Relevance to information need Relevance ranking by IR system Relevance vs. pertinence
Document-Based IRs Input, output, and matching mechanisms Selection of documents (done by indexers) Analysis of documents (done by indexers)
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)
Information Seeking
Process of finding information to fill a knowledge gap User requests Known item searches Unknown item searches Subject searches
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)
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.
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
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
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
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
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
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