Proceedings of the ACM SIGIR 2005 Workshop on Information Retrieval in Context (IRiX)

Copyright of the works contained within this volume remains with the respective authors. Preface IR research is now conducted in multi-media, multilingual , and multi-modal environments but largely in a context-free manner. However, the retrieval of such information will depend on time, place, history of interaction, task in hand, and a range of other factors that are not given explicitly but are implicit in the interaction and ambient environment, namely the context. Such contextual data can be used effectively to constrain retrieval of information thereby reducing the complexity of the retrieval process. Context implies interactive IR and there may exist a stratification of contexts in association to IR engines and systems. Such strata range from the traditional content features of and between information objects, like words nested in paragraphs and hyperlinks, over eye and mouse movements during session-time into the searcher's current work or daily-life task situation of which IIR forms part. The underlying hypothesis (and belief) is that by taking account of context the next generation of retrieval engines dependent on models of context can be created, designed and developed delivering performance exceeding that of out-of-context engines. Based on the experiences from last years' workshop this 2 nd ACM SIGIR IRiX workshop will focus on three major lines of action that explore the central features or evidence of context: • What are the elements of context that are potentially significant to information retrieval? • Which of these categories/elements are, or could be useful in improving information retrieval? • How can features of context be used to improve information retrieval? Most papers are pertinent to more than one discussion group. Suggestions for preparations for a given discussion group are given as A,B,C below. Please take time to read papers that are relevant to the discussion group you plan to attend. General Terms: IR Theory. INTRODUCTION IR research is now conducted in multi-media, multilingual, and multi-modal environments but largely in a context-free manner. However, the retrieval of such information will depend on time, place, history of interaction, task in hand, and a range of other factors that are not given explicitly but are implicit in the interaction and ambient environment, namely the context. Such contextual data can be used effectively to constrain retrieval of information thereby reducing the complexity of the retrieval process. Context implies interactive IR and there exist a stratification of contexts in association to IR engines and systems …

[1]  Jimmy J. Lin,et al.  Knowledge Extraction for Clinical Question Answering: Preliminary Results , 2005 .

[2]  Kalervo Järvelin,et al.  Task complexity affects information seeking and use , 1995 .

[3]  Stephen E. Robertson,et al.  Okapi at TREC-5 , 1996, TREC.

[4]  Peter Ingwersen,et al.  Information Retrieval in Contexts , 2004 .

[5]  Ivan Burmistrov,et al.  Do Interrupted Users Work Faster or Slower? The Micro-analysis of Computerized Text Editing Task , 2003 .

[6]  Peter Ingwersen,et al.  Information retrieval in context: IRiX , 2005, SIGF.

[7]  Charles L. A. Clarke,et al.  Modeling task-genre relationships for IR in the workplace , 2005, SIGIR '05.

[8]  Inger Askehave,et al.  What are the Characteristics of Digital Genres? - Genre Theory from a Multi-Modal Perspective , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[9]  Janice Langan-Fox,et al.  Process in skill acquisition: motivation, interruptions, memory, affective states, and metacognition , 2002 .

[10]  Barbara M. Wildemuth,et al.  The effects of domain knowledge on search tactic formulation , 2004, J. Assoc. Inf. Sci. Technol..

[11]  Douglas C. Engelbart,et al.  Augmenting human intellect: a conceptual framework , 1962 .

[12]  Jennifer Widom,et al.  Scaling personalized web search , 2003, WWW '03.

[13]  Xiangji Huang,et al.  A dual index model for contextual information retrieval , 2005, SIGIR '05.

[14]  Amanda Spink,et al.  Issues of context in information retrieval (IR): an introduction to the special issue , 2002, Inf. Process. Manag..

[15]  Andreas F. Ehmann,et al.  Mining Music Reviews: Promising Preliminary Results , 2005, ISMIR.

[16]  Amanda Spink,et al.  An Analysis of Web Documents Retrieved and Viewed , 2003, International Conference on Internet Computing.

[17]  Anne Gilliland-Swetland,et al.  Introduction to Metadata: Pathways to Digital Information , 1998 .

[18]  Ryen W. White,et al.  A Simulated Study of Implicit Feedback Models , 2004, ECIR.

[19]  Scott Nicholson,et al.  Bibliomining for automated collection development in a digital library setting: Using data mining to discover Web-based scholarly research works , 2003, J. Assoc. Inf. Sci. Technol..

[20]  Jussi Karlgren,et al.  Web-Specific Genre Visualization , 1998, WebNet.

[21]  Tom Wilson,et al.  Models in Information Behavior Research , 1999 .

[22]  Xuehua Shen,et al.  Context-sensitive information retrieval using implicit feedback , 2005, SIGIR '05.

[23]  John T. Stasko,et al.  Establishing tradeoffs that leverage attention for utility: empirically evaluating information display in notification systems , 2003, Int. J. Hum. Comput. Stud..

[24]  N. Fuhr PAN-Uncovering Plagiarism , Authorship , and Social Software Misuse ImageCLEF 2013-Cross Language Image Annotation and Retrieval INEX-INitiative for the Evaluation of XML retrieval , 2002 .

[25]  Jianchang Mao,et al.  Enterprise Search: Tough Stuff , 2004, ACM Queue.

[26]  J. Stephen Downie,et al.  Toward a Theory of Music Information Retrieval Queries: System Design Implications , 2002, ISMIR.

[27]  Steve Lawrence,et al.  Context in Web Search , 2000, IEEE Data Eng. Bull..

[28]  Chun Wei Choo,et al.  A behavioral model of information seeking on the web: preliminary results of a study of how managers and IT specialists use the web , 1998 .

[29]  Margaret M. Burnett,et al.  Impact of interruption style on end-user debugging , 2004, CHI.

[30]  Djoerd Hiemstra,et al.  Conceptual Language Models for Context-Aware Text Retrieval , 2004, TREC.

[31]  Kara A. Latorella,et al.  The Scope and Importance of Human Interruption in Human-Computer Interaction Design , 2002, Hum. Comput. Interact..

[32]  Ronald Fagin,et al.  Searching the workplace web , 2003, WWW '03.

[33]  James Allan,et al.  The effect of adding relevance information in a relevance feedback environment , 1994, SIGIR '94.

[34]  Ryen W. White,et al.  A study of factors affecting the utility of implicit relevance feedback , 2005, SIGIR '05.

[35]  Peter Ingwersen,et al.  Dimensions of relevance , 2000, Inf. Process. Manag..

[36]  Joseph S. Valacich,et al.  AIS Electronic , 2022 .

[37]  Michael A. Shepherd,et al.  The functionality attribute of cybergenres , 1999, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.

[38]  Ehud Rivlin,et al.  Placing search in context: the concept revisited , 2002, TOIS.

[39]  J. George,et al.  Work Interrupted: A Closer Look at the Role of Interruptions in Organizational Life , 2003 .

[40]  Anne-Marie Vercoustre,et al.  Enterprise PeopleFinder: Combining Evidences from Web Pages and Corporate Data , 2003 .

[41]  Nicholas J. Belkin,et al.  Distributed Expert-Based Information Systems: An Interdisciplinary Approach , 1987, Inf. Process. Manag..

[42]  Jeffrey Pomerantz,et al.  A linguistic analysis of question taxonomies , 2005, J. Assoc. Inf. Sci. Technol..

[43]  Iwan G. J. H. Wopereis,et al.  Differences between novice and experienced users in searching information on the World Wide Web , 2000, J. Am. Soc. Inf. Sci..

[44]  Elaine Toms,et al.  Modeling the information behaviour of software engineers using a work - task framework , 2006, ASIST.

[45]  Wendy A. Kellogg,et al.  "I'd be overwhelmed, but it's just one more thing to do": availability and interruption in research management , 2002, CHI.

[46]  Thorsten Joachims,et al.  Transductive Inference for Text Classification using Support Vector Machines , 1999, ICML.

[47]  Peter Ingwersen,et al.  Information seeking research needs extension toward tasks and technology , 2004, Inf. Res..

[48]  Peter Ingwersen,et al.  Characteristics of scientific Web publications: Preliminary data gathering and analysis , 2004, J. Assoc. Inf. Sci. Technol..

[49]  Wei-Ying Ma,et al.  Probabilistic model for contextual retrieval , 2004, SIGIR '04.

[50]  Sandra G. Hirsh,et al.  Seeking information in order to produce information: An empirical study at Hewlett Packard Labs , 2004, J. Assoc. Inf. Sci. Technol..

[51]  Jerome A Osheroff,et al.  Research Paper: Answering Physicians' Clinical Questions: Obstacles and Potential Solutions , 2005, J. Am. Medical Informatics Assoc..

[52]  Jaime Teevan,et al.  Implicit feedback for inferring user preference: a bibliography , 2003, SIGF.

[53]  Ross Wilkinson,et al.  Generating Personal Travel Guides - And Who Wants Them? , 2001, User Modeling.

[54]  Eugene Volokh,et al.  Personalization and privacy , 2000, CACM.

[55]  D. Lindberg,et al.  The Unified Medical Language System , 1993, Methods of Information in Medicine.

[56]  Anton Leuski Email is a stage: discovering people roles from email archives , 2004, SIGIR '04.

[57]  J. Stephen Downie,et al.  Challenges in Cross-Cultural/Multilingual Music Information Seeking , 2005, ISMIR.

[58]  Marti A. Hearst Improving Full-Text Precision on Short Queries using Simple Constraints , 1996 .

[59]  Steve Cayzer,et al.  Semantic blogging and decentralized knowledge management , 2004, CACM.

[60]  Mark Claypool,et al.  Implicit interest indicators , 2001, IUI '01.

[61]  F. Zijlstra,et al.  Temporal factors in mental work: Effects of interrupted activities , 1999 .

[62]  In-Ho Kang,et al.  Query type classification for web document retrieval , 2003, SIGIR.

[63]  Andrei Broder,et al.  A taxonomy of web search , 2002, SIGF.

[64]  Nicholas J. Belkin,et al.  Reading time, scrolling and interaction: exploring implicit sources of user preferences for relevance feedback , 2001, Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.

[65]  Alexander Pretschner,et al.  Ontology based personalized search , 1999, Proceedings 11th International Conference on Tools with Artificial Intelligence.

[66]  J. Stephen Downie,et al.  How People Describe Their Music Information Needs: A Grounded Theory Analysis Of Music Queries , 2003 .

[67]  Marcelo Fiszman,et al.  The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text , 2003, J. Biomed. Informatics.

[68]  Amanda Spink,et al.  Multitasking information behavior and information task switching: an exploratory study , 2004, J. Documentation.

[69]  Norman J. Brown Speech Acts: An Essay in the Philosophy of Language . By John R. Searle. Cambridge: at the University Press. 1969 Pp. vi, 203. $7.25. , 1970, Dialogue.

[70]  D. Covell,et al.  Information needs in office practice: are they being met? , 1985, Annals of internal medicine.

[71]  Stephen E. Robertson,et al.  Okapi at TREC-3 , 1994, TREC.

[72]  Alan R. Aronson,et al.  Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program , 2001, AMIA.

[73]  ChengXiang Zhai,et al.  Implicit user modeling for personalized search , 2005, CIKM '05.

[74]  P. Gorman,et al.  Can primary care physicians' questions be answered using the medical journal literature? , 1994, Bulletin of the Medical Library Association.

[75]  W. Orlikowski,et al.  Explicit and Implicit Structuring of Genres in Electronic Communication: Reinforcement and Change of Social Interaction , 1999 .

[76]  Jane Greenberg,et al.  Metadata Extraction and Harvesting , 2004 .

[77]  Martin Frank,et al.  The Social Semantic Desktop , 2004 .

[78]  Michael D. Gordon,et al.  Web Search---Your Way , 2001, CACM.

[79]  Anders Ardö,et al.  Focused crawling in the ALVIS semantic search engine , 2005 .

[80]  Víctor M. González,et al.  No task left behind?: examining the nature of fragmented work , 2005, CHI.

[81]  Elaine Toms,et al.  User strategies for handling information tasks in webcasts , 2005, CHI EA '05.

[82]  S. Satya‐Murti Evidence-based Medicine: How to Practice and Teach EBM , 1997 .

[83]  Karen Markey Drabenstott,et al.  Towards a Unified Framework of IR Tasks and Strategies , 2001 .

[84]  W. Bruce Croft,et al.  Task orientation in question answering , 2002, SIGIR '02.

[85]  Jane Greenberg,et al.  Metadata and the world wide web , 2002 .

[86]  K. Bach,et al.  Linguistic Communication and Speech Acts , 1983 .

[87]  William C. Mann,et al.  Rhetorical Structure Theory: Toward a functional theory of text organization , 1988 .

[88]  Alan R. Aronson,et al.  Exploiting a Large Thesaurus for Information Retrieval , 1994, RIAO.

[89]  Vagelis Hristidis,et al.  ObjectRank: Authority-Based Keyword Search in Databases , 2004, VLDB.

[90]  Elaine Toms,et al.  The effect of task domain on search , 2003, CASCON.

[91]  Susan T. Dumais,et al.  Milestones in Time: The Value of Landmarks in Retrieving Information from Personal Stores , 2003, INTERACT.

[92]  Jacqueline Algon The effect of task on the information-related behaviors of individuals in a work-group environment , 1999 .

[93]  Gareth Jones,et al.  The role of context in information retrieval , 2004, SIGIR 2004.

[94]  Wei-Ying Ma,et al.  Probabilistic query expansion using query logs , 2002, WWW '02.

[95]  Yoichi Shinoda,et al.  Information filtering based on user behavior analysis and best match text retrieval , 1994, SIGIR '94.

[96]  Thijs Westerveld,et al.  Structural features in content oriented XML retrieval , 2005, CIKM '05.

[97]  Wolfgang Nejdl,et al.  Activity Based Metadata for Semantic Desktop Search , 2005, ESWC.

[98]  Brian Detlor,et al.  Information Seeking on the Web: An Integrated Model of Browsing and Searching , 2000, First Monday.

[99]  Preben Hansen,et al.  Conceptual framework for tasks in information studies , 2005, J. Assoc. Inf. Sci. Technol..

[100]  Nicholas J. Belkin,et al.  Ask for Information Retrieval: Part I. Background and Theory , 1997, J. Documentation.

[101]  D. Davidson,et al.  The Second Person , 1992 .

[102]  Ingrid Hsieh-Yee Research on Web Search Behavior. , 2001 .

[103]  Peter Ingwersen,et al.  Polyrepresentation of information needs and semantic entities: elements of a cognitive theory for information retrieval interaction , 1994, SIGIR '94.

[104]  Richard Cooper,et al.  Interruptibility as a constraint on hybrid systems , 2004, Minds and Machines.

[105]  Nicholas J. Belkin,et al.  Retrieval techniques , 1987 .

[106]  Peter Ingwersen,et al.  The Turn - Integration of Information Seeking and Retrieval in Context , 2005, The Kluwer International Series on Information Retrieval.

[107]  P. Ingwersen Cognitive Information Retrieval. , 1999 .

[108]  Declan Butler,et al.  Souped-up search engines , 2000, Nature.

[109]  Thorsten Joachims,et al.  Optimizing search engines using clickthrough data , 2002, KDD.

[110]  W. Orlikowski,et al.  Genre Repertoire: The Structuring of Communicative Practices in Organizations , 1994 .

[111]  Ryen W. White,et al.  Evaluating implicit feedback models using searcher simulations , 2005, TOIS.

[112]  Colleen Cool The Concept of Situation in Information Science. , 2001 .

[113]  Pertti Vakkari,et al.  Task-based information searching , 2005, Annu. Rev. Inf. Sci. Technol..

[114]  Yiming Yang,et al.  Introducing the Enron Corpus , 2004, CEAS.

[115]  David Hawking,et al.  Challenges in Enterprise Search , 2004, ADC.

[116]  Louise Limberg,et al.  Experiencing information seeking and learning: a study of the interaction between two phenomena , 1999, Inf. Res..

[117]  Robert S. Taylor,et al.  Information use environments. , 1991 .

[118]  Andrew Trotman,et al.  Narrowed Extended XPath I (NEXI) , 2004, INEX.

[119]  J. Stephen Downie,et al.  Survey Of Music Information Needs, Uses, And Seeking Behaviours: Preliminary Findings , 2004, ISMIR.

[120]  Krishna Bharat SearchPad: explicit capture of search context to support Web search , 2000, Comput. Networks.

[121]  Diane Kelly Understanding implicit feedback and document preference: a naturalistic user study , 2004, SIGF.

[122]  Nicholas J. Belkin,et al.  Categories of Music Description and Search Terms and Phrases Used by Non-Music Experts , 2002, ISMIR.

[123]  Katriina Byström,et al.  Information and information sources in tasks of varying complexity , 2002, J. Assoc. Inf. Sci. Technol..

[124]  Christoph Hölscher,et al.  Web search behavior of Internet experts and newbies , 2000, Comput. Networks.

[125]  Gerard Salton,et al.  Optimization of relevance feedback weights , 1995, SIGIR '95.

[126]  Abigail Sellen,et al.  How knowledge workers use the web , 2002, CHI.

[127]  W. Richardson,et al.  The well-built clinical question: a key to evidence-based decisions. , 1995, ACP journal club.