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Information Retrieval Interaction CMSC 838S Douglas W. Oard April 27, 2006

Information Retrieval Interaction

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Information Retrieval Interaction. CMSC 838S Douglas W. Oard April 27, 2006. Process/System Co-Design. IR System. Query Formulation. Query. Search. Collection Indexing. Index. Collection Acquisition. Collection. System Design. Source Selection. Ranked List. Document - PowerPoint PPT Presentation

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Page 1: Information Retrieval Interaction

Information Retrieval Interaction

CMSC 838SDouglas W. Oard

April 27, 2006

Page 2: Information Retrieval Interaction

Process/System Co-Design

Page 3: Information Retrieval Interaction

System Design

SourceSelection

Search

Query

Document Selection

Ranked List

DocumentExamination

Document

DocumentDelivery

Document

QueryFormulation

IR System

CollectionIndexing Index

CollectionAcquisition Collection

Page 4: Information Retrieval Interaction

Information Needs (Taylor)

• Visceral– What you really want to know

• Conscious– What you recognize that you want to know

• Formalized– How you articulate what you want to know

• Compromised– How you express what you want to know to a system

Page 5: Information Retrieval Interaction

Anomalous State of Knowledge

• Belkin: Searchers do not clearly understand– The problem itself– What information is needed to solve the problem

• The query results from a clarification process

• Dervin’s “sense making”:

Need

Gap Bridge

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Selection/Examination Tasks• “Indicative” tasks

– Recognizing what you are looking for– Determining that no answer exists in a source– Probing to refine mental models of system operation

• “Informative” tasks– Vocabulary acquisition– Concept learning– Information use

Page 7: Information Retrieval Interaction

A Selection Interface Taxonomy• One dimensional lists

– Content: title, source, date, summary, ratings, ...– Order: retrieval status value, date, alphabetic, ...– Size: scrolling, specified number, score threshold

• Two dimensional displays– Construction: clustering, starfield, projection– Navigation: jump, pan, zoom

• Three dimensional displays– Contour maps, fishtank VR, immersive VR

Page 8: Information Retrieval Interaction

Google: KeyWord In Context (KWIC)

Query: University of Maryland College Park

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U Mass: Scrollbar-Tilebar

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NPR Online

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Ask: Suggested Query Refinements

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Vivisimo: Clustered Results

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Kartoo’s Cluster Visualization

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Semantic Maps

• PNL Themescape/Themeview (1995), http://www.pnl.gov/infoviz/technologies.html

• Sandia Vx-Insight (1996), http://www.cs.sandia.gov/projects/VxInsight.html

• Arizona ET-MAP (1998), http://ai.eller.arizona.edu/research/dl/etmapdemo.htm

• Some challenges:– Region labeling– Point labeling

Page 18: Information Retrieval Interaction

Pacific Northwest Lab: ThemeView

Credit to: Pacific Northwest National Laboratory

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LTU ImageSeeker

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Glasgow: “Ostensive” Browser

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CMU: Television News Retrieval

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Maryland: Baltimore Learning CommunityMaryland: Baltimore Learning Community

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Ben’s ‘Seamless Interface’ Principles• Informative feedback• Easy reversal• User in control

– Anticipatable outcomes– Explainable results– Browsable content

• Limited working memory load– Query context– Path suspension

• Alternatives for novices and experts• Scaffolding

Page 25: Information Retrieval Interaction

My ‘Synergistic Interaction’ Principles– Interdependence with process (“interaction models”)

• Co-design with search strategy• Speed

– System initiative• Guided process• Exposing the structure of knowledge

– Support for reasoning• Representation of uncertainty• Meaningful dimensions

– Synergy with features used for search• Weakness of similarity, Strength of language

– Easily learned• Familiar metaphors (timelines, ranked lists, maps)

Page 26: Information Retrieval Interaction

Guidelines for Practice

• Show the query in the selection interface– It provides context for the display

• Explain what the system has done– It is hard to control a tool you don’t understand

• Highlight search terms, for example

• Complement what the system has done– Users add value by doing things the system can’t– Expose the information users need to judge utility