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Using & Evaluating Search EnginesBrowsing and SearchingWhat Is Information Seeking?Information Seeking in ContextSearch StrategiesStudy FindingsModes of ScanningWeb MovesIntegrated Modes & Moves ModelBehavioral Model of Web UseInterview HighlightsBehavioral Model HighlightsPowerPoint PresentationReview of Web Searching StudiesAnalysis of a Very Large Search LogSlide 16Real Life Information RetrievalSlide 18“New” Searching?How can we compare?How Do We Really Use the Web?Design vs. PracticeTaxonomy of Decisions & ActionsTaxonomy pt. 2Human Information BehaviorNew Models of Info Behavior pt. 3Learning and Interests (Users)Slide 28Slide 29Let’s do some searchingUsing & Evaluating Search EnginesUsing & Evaluating Search Engines •Readings-Using Search engines (Google)-Understanding Search-Search Tasks•Let’s do some searching•AssignmentsBrowsing and SearchingBrowsing and Searching•Information Seeking•Using Models•Understanding Navigation•Designing NavigationWhat Is Information Seeking?What Is Information Seeking?•“a process in which humans purposefully engage in order to change their state of knowledge.” p. 5•“a process driven by human’s need for information so that they can interact with the environment.” p. 28•“begins with recognition and acceptance of the problem and continues until the problem is resolved or abandoned” p. 49 Marchionini•more than just representation, storage and systematic retrievalInformation Seeking in ContextInformation Seeking in ContextLearningInformation SeekingInformation RetrievalAnalytical StrategyBrowsingStrategySearch StrategiesSearch Strategies•Analytical•careful planning•recall of query terms•iterative query reformulations•examination of results•batched•Browsing•heuristic•opportunistic•recognizing relevant information•interactive (as can be)Study FindingsStudy Findings-Few participants deliberately set out to search for new sites-Determined the modes of scanning and moves exercised by the participants-Recurring Web behavioral patterns that relate people’s browser actions (Web moves) to their browsing/searching context (Web modes)-Modes of scanning: Aguilar (1967) & Weick & Daft (1983, 1984)-Moves in information seeking behavior: Ellis (1989) & Ellis et. al. (1993, 1997)Modes of ScanningModes of ScanningScanning Modes Information Need Information Use Amount of Targeted Effort Number of Sources Tactics Undirected Viewing General areas of interest; specific need to be revealed Serendipitous discovery “Sensing ” Minimal Many • Scan broadly a diversity of sources, taking advantage of what’s easily accessible • “Touring ” Conditioned Viewing Able to recognize topics of interest Increase understanding “Sensemaking ” Low Few • Browse in pre -selected sources on pre -specified topics of interest • “Tracking ” Infor mal Search Able to formulate queries Increase knowledge within narrow limits “Learning ” Medium Few • Search is focused on an issue or event, but a good -enough search is satisfactory • “Satisficing ” Formal Search Able to specify targets Formal use of information for planning, acting “Deciding ” High Many • Systematic gathering of information on a target, following some method or procedure • “Retrieving ”Web MovesWeb MovesIntegrated Modes & Moves ModelIntegrated Modes & Moves Model StartingChainingBrowsingDifferentiatingMonitoring ExtractingUndirectedViewingIdentifyingselectingstartingpages, sitesFollowinglinks oninitialpages ConditionedViewing Browsingentrypages,headings,site mapsBookmarking,printing,copyingGoing directlyto known siteRevisiting‘favorite’ orbookmarkedsites for newinformation InformalSearch Bookmarking,printing,copyingGoing directlyto known siteRevisiting‘favorite’ orbookmarkedsites for newinformationUsing(local)searchengines toextractinformationFormalSearch Revisiting‘favorite’ orbookmarkedsites for newinfoUsingsearchengines toextractinformationBehavioral Model of Web UseBehavioral Model of Web Use•61 identifiable episodes•Confirmed in Interviews Starting Chaining Browsing Differentiating Monitoring Extracting Undirected Viewing Conditioned Viewing Informal Search Formal Search 12 Episodes 18 Episodes 23 Episodes 8 EpisodesInterview HighlightsInterview Highlights•Most useful work-related sites:1. Resource sites by associations & user groups2. News sites 3. Company sites4. Search engines•Most people do not avidly search for new Web sites•Criteria to bookmark a site is largely based on a site’s ability to provide relevant & up-to-date information•Methods for identifying new Web sites:1. Search engines2. Magazines & newsletters3. Other people/colleaguesBehavioral Model HighlightsBehavioral Model Highlights•People who use the Web engage in 4 complementary modes of information seeking•Certain browser based actions & events indicate a particular mode of information seeking•Surprises-No Explicit Instances of Monitoring to Support Formal Searching-Very Few Instances of “Push” Monitoring-Extracting Involved Basic Search Strategies OnlyReview of Web Searching StudiesReview of Web Searching Studies•How robust is the field of Web Search studies?•What are the common approaches to studying Web use?•Are all Web searchers the same?-How?-Why not?•“Isolating searching characteristics of search using a Web IR system via analysis of data, typicaly gathers from transaction logs” p. 236Analysis of a Very Large Search LogAnalysis of a Very Large Search Log•280 GB – Six Weeks of Web Queries•1 Billion Search Requests•285 Million User Sessions•Web Users:-Use Short Queries-Mostly Look at the First Ten Results only-Seldom Modify Queries•Traditional IR Isn’t Accurately Describing Web Search•Phrase Searching Could Be Augmented•Silverstein, Henzinger, Marais, Moricz (1998)Analysis of a Very Large Search LogAnalysis of a Very Large Search Log•2.35 Average Terms Per Query-0 = 20.6% (?)-1 = 25.8%-2 = 26.0% = 72.4%•Operators Per Query-0 = 79.6%•Terms Predictable•First Set of Results Viewed Only = 85%•Some (Single Term Phrase) Query Correlation -Augmentation-Taxonomy Input-Robots vs. HumansReal Life Information RetrievalReal Life Information Retrieval•51K Queries from Excite (1997)•Search Terms = 2.21•Number of Terms-1 = 31% -2 = 31% -3 = 18% (80% Combined)•Logic & Modifiers (by


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UT CE 385 - Using & Evaluating Search Engines

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