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

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Presentation on theme: "Information in the Digital Environment Information Seeking Models Dr. Dania Bilal IS 530 Spring 2005."— Presentation transcript:

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

2 Information Options  Print  CD-ROM databases  Remote databases (e.g., Dialog)  Web

3 Print Option  Inexpensive  Owned by library  Easily accessible

4 CD-ROM Databases  Purchase or lease  Subscription  Library responsible for software & hardware  Most common is CD-ROM

5 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

6 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

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

8 Information Retrieval System (IR)  A set of components that interact to provide feedback  Comprised of interlinked entities Agency that creates the databases People Documents

9 Interlinked Entities Agency Documents People

10 IR Information Transfer  Inputs  Processes  Objectives of the system  Outputs

11 The IR Cycle

12  Documents are analyzed, translated, indexed, and stored.  Documents are organized Cataloging (description/representation of docs.) Subject indexing

13 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

14 The IR Cycle  Language of the system (controlled vocabulary) List of subject headings (Pre-coordinate) Thesauri (Pre-coordinate) Classification scheme

15 The IR Cycle  Documents are represented by other entities Author(s) Date of publication Language Identifiers

16 The IR Cycle  Entities may become access points  Documents are stored after indexing  Document representation is entered into the matching mechanism

17 The IR Cycle  A file of document surrogates is established  File becomes available for searching using a variety of access points

18 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

19 Explanation of the IR Cycle  Output A set of records found and deemed relevant to a user query  User judgment of retrieval

20 User Judgment  Relevance to information need  Relevance ranking by IR system  Relevance vs. pertinence

21 Document-Based IRs  Input, output, and matching mechanisms  Selection of documents (done by indexers)  Analysis of documents (done by indexers)

22 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)

23 Information Seeking

24  Process of finding information to fill a knowledge gap  User requests Known item searches Unknown item searches  Subject searches

25 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)

26 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.

27 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

28 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

29 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

30 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

31 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

32 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


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