Information Retrieval in Context of Digital Libraries - or DL in Context of IR

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Information Retrieval in Context of Digital Libraries - or DL in Context of IR. Peter Ingwersen Royal School of LIS Denmark pi@db.dk http://www.db.d/pi. Agenda. Information Retrieval In Context of Information Behavior Laboratory Model = Digital Library approach? - PowerPoint PPT Presentation

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  • Information Retrieval in Context of Digital Libraries- or DL in Context of IRPeter IngwersenRoyal School of LISDenmark pi@db.dkhttp://www.db.d/pi

    LIDA 2009

  • LIDA 2009*IngwersenAgendaInformation RetrievalIn Context of Information BehaviorLaboratory Model = Digital Library approach?Integrated Model roles of contextThe social perspective Challenges in IR / DL according to modelConclusions

    LIDA 2009

  • LIDA 2009*IngwersenInformation RetrievalThe processes involved in the representation, storage, searching, finding, filtering, presentation and use of information relevant to a requirement for information desired by a human user (The Turn, 2005)Interaction Time dimension

    LIDA 2009

  • LIDA 2009*IngwersenInformation behaviour and IR

    T. Wilsons Onion Model, 1999 - extended:Seeking

    IRJob-relatedWork TasksInterestsNon-job-relatedTasks and InterestsDaily-life behavior

    Information behaviourInteractiveIRBehaviour

    LIDA 2009

  • LIDA 2009*IngwersenInformation behaviour and other central concepts in Information StudiesInformation behaviour:to create information e.g., on the Net - blogs; also human indexing, including social tagging; to produce publications e.g., as publisherto communicate face-to-face; chat; e-mailto manage information sources e.g. KM; selectivity

    LIDA 2009

  • IB and other central concepts Information seeking (behaviour)Information behaviour with interest for InformationInformation need exist even muddled or exploratorySearching information sources e.g. colleagues Information Retrieval (I)IRSearching information space via systems Digital Library & Assets (interactive IR)Retrieval models; relevance feedback & ranking; query modification; auto indexing and weighting; LIDA 2009*Ingwersen

    LIDA 2009

  • LIDA 2009*IngwersenThe Laboratory Model of IR(in the Cranfield-TREC Laboratory Research Framework)Could just as well be a model for Digital Library developmentDocu-mentsPseudoRelevanceFeedback

    LIDA 2009

  • The Lab IR Cave, with a VisitorThe Turn Ingwersen & Jrvelin, 2005Docu-mentsRepresen-tationDatabaseSearchrequestQueryMatchingRepresen-tationQueryResultContext

    LIDA 2009

  • LIDA 2009*IngwersenSimplistic model of (I)IR short-term interaction in context

    LIDA 2009

  • LIDA 2009*IngwersenIngwersenCentral Components of Interactive IR the basic Integrated Framework The Lab./DL FrameworkIn situ recommendationIn situ tagging

    LIDA 2009

  • LIDA 2009*IngwersenIngwersenIntegrated Framework and Relevance Criteria

    LIDA 2009

  • LIDA 2009*IngwersenMoving into ContextStrength:Involvement of TASK (work/search) and Processes for fulfillment of task and Task result / outcomeSeeking and retrieval tasks influenced by work tasksPointing to novel relevance measuresTask fulfillment measures; socio-cognitive relevance; social utility (tagging, visits, downloads )

    LIDA 2009

  • LIDA 2009*IngwersenChallenges to IR/DL[If] we consider that unlike art IR is not there for its own sake then IR is far, far more than a branch of computer scienceAnd what information and relevance means to IR, Tefko Saracevic states (1997, p. 17) [In] broadest sense: Information is that involves not only messages (first sense) that are cognitively processed (second sense), but also a context a situation, task, problem-at-hand, the social horizon, intentions

    LIDA 2009

  • LIDA 2009*IngwersenChallenges to IR/DL 2Understanding actors goals, tasks intentions in diversity of contextsJob-related knowledge enquiries Daily-life information explorative behaviorsEntertainment - or simply meaning makingInference of goals, tasks, intentions from implicit evidence from interaction behaviorImplicit relevance feedback study examples

    LIDA 2009

  • LIDA 2009*IngwersenChallenges to IR/DL 3Leading to finding out the best algorithmic models and solutions not in themselves but given understanding of characteristics of searcher goals, A lot of searching is undirected, vague, random, exploratory, muddled (Skov, 2009)A lot of tagging (and folksonomies) is randomly done - but can be filtered

    LIDA 2009

  • LIDA 2009*IngwersenChallenges to IR/DL 4Belkin, Nick. Sigir Forum, 42(1), 2008: 47-54Recommender systems and personalization are relying on a narrow conception, applying vague correlations between a current searchers situation and previous Dwell time on page;Click-throughViewed, rated or saved objects by other searchersSearch profiles contentsTo tailor the rank of search resultsOr to find things alike (probably better)

    LIDA 2009

  • LIDA 2009*IngwersenChallenges to IR/DL 5Which of the (personal) contextual features do we need to involve incl. the IT context?How to present retrieved and filtered documents?Zooming in/out integrated searching of media & document types: presentation form and relevance/usability:Are interface issues solved by Google snippets and Microsofts detail-whole format?Alternative (elaborated) evaluation methods for interaction design (IR/DL) are required

    LIDA 2009

  • LIDA 2009*IngwersenThe Circle of Systemic/Social Contexts in interaction design: Digital Libraries & (I)IR actor as centreInter-faceSocial InteractionIR Interaction

    LIDA 2009

  • LIDA 2009*IngwersenConclusionsIR and DL (or Digital Assets including museums and cultural heritage) face same challenges of addressing the Interactive nature of the information processContexts and their limitsEvaluation & research approachesNeed for combined efforts of IT and behavior

    LIDA 2009

  • LIDA 2009*IngwersenThank You!

    LIDA 2009

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