Advances in Information Retrieval: 28th European Conference by Mounia Lalmas, Andrew MacFarlane, Stefan Rüger, Anastasios

By Mounia Lalmas, Andrew MacFarlane, Stefan Rüger, Anastasios Tombros, Theodora Tsikrika, Alexei Yavlinsky

th those complaints comprise the refereed papers and posters provided on the 28 Annual ecu convention on details Retrieval (ECIR 2006), which used to be held at Imperial university London in South Kensington among April 10 and 12, 2006. ECIR is the yearly convention of the British laptop Society’s Inf- mation Retrieval expert staff. the development began its lifestyles 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. when you consider that then the venue has alternated among the united kingdom and Continental Europe. within the final decade ECIR has grown to turn into the most important Europeanforumforthediscussionofresearchinthe?eldofinformationretrieval. ECIR 2006 acquired 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 authorized, and papers have been switched over to posters. All contributions have been reviewed by means of no less than 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 reliable and fit signal for info retrieval as a rule, and ECIR particularly, that the submission expense has greater than doubled during the last 3 years. the drawback, in fact, is that many top quality submissions needed to be rejected as a result of a constrained skill of the conference.

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Extra info for Advances in Information Retrieval: 28th European Conference on IR Research, ECIR 2006, London, UK, April 10-12, 2006. Proceedings

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Let G={A, B, D} as a weighted graph constructed by A, B and D. = A U B is the vertex set while D = {d ij } is the edge set. WA, WB are the B B B B total weights of A, B respectively. In the weighted graph G, the set of all feasible flows ξ = [fij] from A to B is defined by the following constraints: B B f ij ≥ 0 1 ≤ i ≤ m 1 ≤ j ≤ n n ∑f j =1 m ∑f i =1 ij 1≤ i ≤ m = wai ij = wbj WA WB m n ∑∑ i =1 j =1 (8) (9) 1≤ j ≤ n (10) f ij = WA (11) Constraint (8) allows moving words from A to B and not vice versa.

Also, the optimal value of the LM parameter µ tends to be larger for long queries than for short queries. They observe that smoothing plays a more important role for long queries than for short queries. They also observe that Dirichlet prior performs worse on long queries than title queries on the web collection. In particular, for each subcollection contained in the 2GB collection the optimal value of µ varies from 500 to 4000 for the short queries and from 2000 to 5000 for the long queries. They conclude that the optimal value of µ depends both on the collection and the verbosity of the query.

For example, it naturally extends the notion of a similarity distance between subtopics to that of a similarity B B B B 32 X. Wan and J. Yang distance between subtopic sets, or documents by allowing for many-to-many matches among subtopics according to their similarity. The PTD is calculated by first dividing, for both point sets, every point’s weight by its point set’s total weight, and then calculating the EMD for the resulting point sets. Efficient algorithms for the transportation problem are available, which are important to compute EMD efficiently.

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