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Authors: Peiling Wang and Dagobert Soergel Reviewer: Douglas W. Oard

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Presentation on theme: "Authors: Peiling Wang and Dagobert Soergel Reviewer: Douglas W. Oard"— Presentation transcript:

1 A Cognitive Model of Document Use During a Research Project (Study I: Document Selection)
Authors: Peiling Wang and Dagobert Soergel Reviewer: Douglas W. Oard LBSC 878, Session 2, February 4, 2001

2 Outline Methodology Model Results Implications

3 Qualitative Methodology
Conditions University agriculture library users Dialog search Procedure Think aloud protocol Anchored tri-state judgments Analysis Theory-guided emergent coding scheme Discussion questions: How transferable would this study be to: 1) Other users (e.g., engineers)? 2) Other collections (e.g., the Web)? 3) Other modalities (e.g., television shows)? Why are tri-state judgments important?

4 A Decision Theory Model
Decision is a function of criteria Decision: retrieve or don’t retrieve They explain the function using “decision rules” and “values” A criterion is a function of evidence (DIE) e.g., journal can provide evidence for quality Discussion questions: Given Wilson’s definitions of “true relevence” and “perceived relevance,” which kind of relevance underlies Wang and Soergel’s decision theory model? Wang and Soergel adopt what we will call a “combination of evidence” strategy in which many types of evidence contributes to the basis for assessing relevance. Does this correspond more closely to Wilson’s definition of logical relevance or of evidential relevance?

5 Criteria Cases with at least 2% shown Notes:
Unmentioned criteria cannot be discovered using this methodology Cases with at least 2% shown

6 Sources of Evidence Percent: Cases with at least 4% shown

7 Decision Rules Cases with at least 2% shown

8 Values Cases with at least 2% shown
Functional: Matches Soergel’s definition of pertinence Epistemic: Useful as background knowledge Conditional: Might become pertinent Social: Provides information that enables personal relationships Cases with at least 2% shown

9 Implications for Design
Query interface Allow specification of selection criteria Search Embed knowledge about journal quality, etc. Document selection Emphasize evidence that facilitates rejection Cluster (possibly) chained documents Feedback Let user indicate evidence that caused a decision


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