By Gary Marchionini (auth.), Sharon McDonald, John Tait (eds.)
Theseproceedingscontaintherefereedfulltechnicalpaperspresentedatthe26th Annual eu convention on details Retrieval (ECIR 2004). ECIR is theannualconferenceoftheBritishComputerSociety’sspecialistgroupinInf- mation Retrieval. This 12 months the convention was once held on the institution of Computing and expertise on the collage of Sunderland. ECIR started lifestyles because the - nual Colloquium on info Retrieval examine. The colloquium was once held within the united kingdom every year until eventually 1998 whilst the development was once held in Grenoble, France. considering that then the convention venue has alternated among the uk and Continental Europe, and the development was once renamed the ecu convention on info Retrieval. lately, ECIR has persevered to develop and has turn into the key ecu discussion board for the dialogue of analysis within the ?eld of data Retrieval. To mark this metamorphosis from a small casual c- loquium to an important occasion within the IR learn calendar, the BCS-IRSG determined to rename the development to the ecu convention on info Retrieval. ECIR2004received88fullpapersubmissions,fromacrossEuropeandfurther a?eldincludingNorthAmerica,ChinaandAustralia,atestamenttothegrowing acceptance and attractiveness of the convention. Out of the 88 submitted papers, 28 have been permitted for presentation. All papers have been reviewed through at the least 3 reviewers. one of the authorised papers eleven have a pupil because the fundamental writer, illustrating that the normal pupil concentration of the unique colloquium is alive today.
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Additional info for Advances in Information Retrieval: 26th European Conference on IR Research, ECIR 2004, Sunderland, UK, April 5-7, 2004. Proceedings
It is often difficult to assess how a technique will actually perform in “real-life” because of a lack of a user-centered evaluation metric. Instead, assumptions must be made about how a user would classify, label and evaluate documents. In the paper, we evaluate the accuracy of two language model-based clustering techniques with user-defined topic classes of web pages from personal web browsing histories. We further investigate the effectiveness of including behavioral evidence in the construction of these models.
Wilks Sparck Jones, K. 1999a. What is the role of NLP in text retrieval. ) Natural language Information Retrieval. Kluwer: New York. Sparck Jones, K. 1999b. Information Retrieval and Artificial Intelligence. Artificial Intelligence Journal, vol. 114. Stevenson, M. and Wilks, Y. 1999. Combining Weak Knowledge Sources for Sense Disambiguation Proceedings of the International Joint Conference for Artifical Intelligence (IJCAI-99) Strzalkowski, T. and B. Vauthey, 1991. Natural Language Processing in Automated Information Retrieval, PROTEUS Project Memorandum.
Borillo, A, Virbel, J and Siot-Decauville, N. 1970. Procedures d’analyse semantique appliquees a la documentation scientifique. Gauthier-Villars: Paris. , Lafferty, J. 1999. Information retrieval as statistical translation. SIGIR 1999. Berger, A. et al. 2000. Bridging the lexical chasm: statistical approaches to question answering. SIGIR 2000. , and Weischedel R. 1997. Nymble: a High-Performance Learning Name-finder. In Proceedings of the Fifth conference on Applied Natural Language Processing.
Advances in Information Retrieval: 26th European Conference on IR Research, ECIR 2004, Sunderland, UK, April 5-7, 2004. Proceedings by Gary Marchionini (auth.), Sharon McDonald, John Tait (eds.)