By Mounia Lalmas, Andrew MacFarlane, Stefan Rüger, Anastasios Tombros, Theodora Tsikrika, Alexei Yavlinsky
th those court cases include the refereed papers and posters provided on the 28 Annual eu convention on details Retrieval (ECIR 2006), which used to be held at Imperial collage London in South Kensington among April 10 and 12, 2006. ECIR is the yearly convention of the British desktop Society’s Inf- mation Retrieval professional workforce. the development began its existence as a colloquium in 1978 and was once held within the united kingdom every year till 1998, whilst the development came about in Grenoble, France. in view that then the venue has alternated among the united kingdom and Continental Europe. within the final decade ECIR has grown to turn into the foremost Europeanforumforthediscussionofresearchinthe?eldofinformationretrieval. ECIR 2006 bought 177 paper and seventy three poster submissions, mostly from the united kingdom (18%) and Continental Europe (50%), yet we had many sub- missions from furthera?eldincludingAmerica(7%),Asia(21%),Middle EastandAfrica(2%), and Australasia (2%). In overall 37 papers and 28 posters have been approved, and papers have been switched over to posters. All contributions have been reviewed through a minimum of 3 reviewers in a double nameless procedure after which ranked in the course of a ProgrammeCommittee assembly with respectto scienti?c caliber andoriginality. it's a strong and fit signal for info retrieval often, and ECIR specifically, that the submission cost has greater than doubled during the last 3 years. the disadvantage, after all, is that many top of the range submissions needed to be rejected because of a constrained potential of the conference.
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Additional resources for Advances in Information Retrieval: 28th European Conference on IR Research, ECIR 2006, London, UK, April 10-12, 2006. Proceedings
1 Types of Urns We may classify IR models according to the way we interpret the stratification of the population . We can imagine an ordinary sampling experiment as the selection of balls from a single urn, in general with replacement and shuffling. This is called a Type I model. We may select before a urn at a random, and then make an experiment as described by a Type I model. The urn selection generates a Type II model. Type III model is similarly defined. Translating this hierarchy to IR, we may say – IR model of Type I.
Information Retrieval. Butterworths, London (1979) 19. Wan, X. , and Peng, Y. : A new retrieval model based on TextTiling for document similarity search. Journal of Computer Science & Technology 20-4 (2005) 552-558. 20. Xiao, W. : Graph Theory and Its Algorithms. Beijing: Aviation Industry Press (1993) 21. : Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering. In Proc. of 25th SIGIR conference (2002) 113-120 22. : A study of smoothing methods for language models applied to ad hoc information retrieval.
Wan and J. Yang document should be allowed to be matched to more than one subtopic in the other document with different weights, and thus the many-to-many matching is allowed between the subtopics of two documents. In this study we propose a novel measure based on the Proportional Transportation Distance (PTD) to evaluate document similarity by allowing many-to-many matching between subtopics. First, documents are decomposed into sets of subtopics, each subtopic being represented by a contiguous or incontiguous block of text, and then the Proportional Transportation Distance is employed to evaluate the similarity between two sets of subtopics for two documents by solving a transportation problem.
Advances in Information Retrieval: 28th European Conference on IR Research, ECIR 2006, London, UK, April 10-12, 2006. Proceedings by Mounia Lalmas, Andrew MacFarlane, Stefan Rüger, Anastasios Tombros, Theodora Tsikrika, Alexei Yavlinsky