By Maarten de Rijke, Tom Kenter, Arjen P. de Vries, ChengXiang Zhai, Franciska de Jong, Kira Radinsky, Katja Hofmann
This publication constitutes the complaints of the thirty sixth ecu convention on IR examine, ECIR 2014, held in Amsterdam, The Netherlands, in April 2014.
The 33 complete papers, 50 poster papers and 15 demonstrations provided during this quantity have been conscientiously reviewed and chosen from 288 submissions. The papers are equipped within the following topical sections: review, advice, optimization, semantics, aggregation, queries, mining social media, electronic libraries, potency, and data retrieval thought. additionally incorporated are three educational and four workshop presentations.
Read Online or Download Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014. Proceedings PDF
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Extra info for Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014. Proceedings
The EM algorithm iteratively estimates two sets of values: the hidden variables, which are the pseudo-judgment scores for each document on each topic; and the parameters, which are the loss-minimizing weights for each system. For each document Dm,n , a real-valued pseudo-judgment Jm,n reflects the EM algorithm’s current degree of belief that document n is relevant to topic m. Similarly, the system weight w j represents the algorithm’s present degree of belief that the results produced by system j are correct.
Some simple eﬀective approx. to the 2-poisson model for probabilistic weighted retrieval. In: Proc. of ACM SIGIR 1994, pp. 232–241 (1994) 19. : A vector space model for automatic indexing. Communications of the ACM 18(11), 613–620 (1975) 20. : Automatic Information Organization and Retrieval (1968) 21. : Pivoted document length normalization. In: Proce. of the 19th ACM SIGIR Conference, SIGIR 1996, pp. 21–29 (1996) 22. : Relating retrievability, performance and length. In: Proc. of the 36th ACM SIGIR Conference, SIGIR 2013, pp.
Ap by percent of pooled judgment used for different TREC Ad Hoc collections Table 3. 4 The computational complexity of our proposed EM-based method is O(CST n), where S is the number of systems, T the number of topics, n the number of unique documents for a topic in the pool, and C the number of iterations before the convergence. Empirically, C is smaller than 40. The time complexity of RTC is O(S2 T n3 ). 9; the results are reported on MAP@1k; the unjudged documents are considered as not relevant; losses are transformed linearly into the range of [0,1]; for each topic, there will be one document selected to be judged in each iteration.