-
Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002)
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-
Blandford, A.; Adams, A.; Attfield, S.; Buchanan, G.; Gow, J.; Makri, S.; Rimmer, J.; Warwick, C.: ¬The PRET A Rapporter framework : evaluating digital libraries from the perspective of information work (2008)
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-
Abdou, S.; Savoy, J.: Searching in Medline : query expansion and manual indexing evaluation (2008)
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- Abstract
- Based on a relatively large subset representing one third of the Medline collection, this paper evaluates ten different IR models, including recent developments in both probabilistic and language models. We show that the best performing IR models is a probabilistic model developed within the Divergence from Randomness framework [Amati, G., & van Rijsbergen, C.J. (2002) Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM-Transactions on Information Systems 20(4), 357-389], which result in 170% enhancements in mean average precision when compared to the classical tf idf vector-space model. This paper also reports on our impact evaluations on the retrieval effectiveness of manually assigned descriptors (MeSH or Medical Subject Headings), showing that by including these terms retrieval performance can improve from 2.4% to 13.5%, depending on the underling IR model. Finally, we design a new general blind-query expansion approach showing improved retrieval performances compared to those obtained using the Rocchio approach.
-
Iivonen, M.: Consistency in the selection of search concepts and search terms (1995)
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- Abstract
- Considers intersearcher and intrasearcher consistency in the selection of search terms. Based on an empirical study where 22 searchers from 4 different types of search environments analyzed altogether 12 search requests of 4 different types in 2 separate test situations between which 2 months elapsed. Statistically very significant differences in consistency were found according to the types of search environments and search requests. Consistency was also considered according to the extent of the scope of search concept. At level I search terms were compared character by character. At level II different search terms were accepted as the same search concept with a rather simple evaluation of linguistic expressions. At level III, in addition to level II, the hierarchical approach of the search request was also controlled. At level IV different search terms were accepted as the same search concept with a broad interpretation of the search concept. Both intersearcher and intrasearcher consistency grew most immediately after a rather simple evaluation of linguistic impressions
-
Crestani, F.; Rijsbergen, C.J. van: Information retrieval by imaging (1996)
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- Source
- Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
-
Leininger, K.: Interindexer consistency in PsychINFO (2000)
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- Date
- 9. 2.1997 18:44:22
-
Reichert, S.; Mayr, P.: Untersuchung von Relevanzeigenschaften in einem kontrollierten Eyetracking-Experiment (2012)
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- Date
- 22. 7.2012 19:25:54
-
Keenan, S.; Smeaton, A.F.; Keogh, G.: ¬The effect of pool depth on system evaluation in TREC (2001)
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-
Vegt, A. van der; Zuccon, G.; Koopman, B.: Do better search engines really equate to better clinical decisions? : If not, why not? (2021)
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-
Belkin, N.J.: ¬An overview of results from Rutgers' investigations of interactive information retrieval (1998)
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- Date
- 22. 9.1997 19:16:05
-
King, D.W.: Blazing new trails : in celebration of an audacious career (2000)
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- Date
- 22. 9.1997 19:16:05
-
Petrelli, D.: On the role of user-centred evaluation in the advancement of interactive information retrieval (2008)
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- Source
- Information processing and management. 44(2008) no.1, S.22-38
-
Pal, S.; Mitra, M.; Kamps, J.: Evaluation effort, reliability and reusability in XML retrieval (2011)
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- Date
- 22. 1.2011 14:20:56
-
Chu, H.: Factors affecting relevance judgment : a report from TREC Legal track (2011)
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- Date
- 12. 7.2011 18:29:22
-
Wildemuth, B.; Freund, L.; Toms, E.G.: Untangling search task complexity and difficulty in the context of interactive information retrieval studies (2014)
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- Date
- 6. 4.2015 19:31:22
-
Ravana, S.D.; Taheri, M.S.; Rajagopal, P.: Document-based approach to improve the accuracy of pairwise comparison in evaluating information retrieval systems (2015)
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- Date
- 20. 1.2015 18:30:22
-
Rajagopal, P.; Ravana, S.D.; Koh, Y.S.; Balakrishnan, V.: Evaluating the effectiveness of information retrieval systems using effort-based relevance judgment (2019)
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- Date
- 20. 1.2015 18:30:22
-
Lioma, C.; Ounis, I.: ¬A syntactically-based query reformulation technique for information retrieval (2008)
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- Abstract
- Whereas in language words of high frequency are generally associated with low content [Bookstein, A., & Swanson, D. (1974). Probabilistic models for automatic indexing. Journal of the American Society of Information Science, 25(5), 312-318; Damerau, F. J. (1965). An experiment in automatic indexing. American Documentation, 16, 283-289; Harter, S. P. (1974). A probabilistic approach to automatic keyword indexing. PhD thesis, University of Chicago; Sparck-Jones, K. (1972). A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28, 11-21; Yu, C., & Salton, G. (1976). Precision weighting - an effective automatic indexing method. Journal of the Association for Computer Machinery (ACM), 23(1), 76-88], shallow syntactic fragments of high frequency generally correspond to lexical fragments of high content [Lioma, C., & Ounis, I. (2006). Examining the content load of part of speech blocks for information retrieval. In Proceedings of the international committee on computational linguistics and the association for computational linguistics (COLING/ACL 2006), Sydney, Australia]. We implement this finding to Information Retrieval, as follows. We present a novel automatic query reformulation technique, which is based on shallow syntactic evidence induced from various language samples, and used to enhance the performance of an Information Retrieval system. Firstly, we draw shallow syntactic evidence from language samples of varying size, and compare the effect of language sample size upon retrieval performance, when using our syntactically-based query reformulation (SQR) technique. Secondly, we compare SQR to a state-of-the-art probabilistic pseudo-relevance feedback technique. Additionally, we combine both techniques and evaluate their compatibility. We evaluate our proposed technique across two standard Text REtrieval Conference (TREC) English test collections, and three statistically different weighting models. Experimental results suggest that SQR markedly enhances retrieval performance, and is at least comparable to pseudo-relevance feedback. Notably, the combination of SQR and pseudo-relevance feedback further enhances retrieval performance considerably. These collective experimental results confirm the tenet that high frequency shallow syntactic fragments correspond to content-bearing lexical fragments.
-
Larsen, B.; Ingwersen, P.; Lund, B.: Data fusion according to the principle of polyrepresentation (2009)
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- Date
- 22. 3.2009 18:48:28
