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Information Retrieval Interaction CMSC 838S Douglas W. Oard April 27, 2006
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Process/System Co-Design
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System Design Source Selection Search Query Document Selection Ranked List Document Examination Document Delivery Document Query Formulation IR System Collection Indexing Index Collection Acquisition Collection
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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
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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 GapBridge
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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
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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
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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 http://www.pnl.gov/infoviz/technologies.html Sandia Vx-Insight (1996), http://www.cs.sandia.gov/projects/VxInsight.html http://www.cs.sandia.gov/projects/VxInsight.html Arizona ET-MAP (1998), http://ai.eller.arizona.edu/research/dl/etmapdemo.htm http://ai.eller.arizona.edu/research/dl/etmapdemo.htm Some challenges: –Region labeling –Point labeling
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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 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
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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)
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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
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