-
Belkin, N.J.; Cabezas, A.; Cool, C.; Kim, K.; Ng, K.B.; Park, S.; Pressman, R.; Rieh, S.; Savage, P.; Xie, H.: Rutgers interactive track at TREC-5 (1997)
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Ng, K.B.; Loewenstern, D.; Basu, C.; Hirsh, H.; Kantor, P.B.: Data fusion of machine-learning methods for the TREC5 routing tak (and other work) (1997)
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- Date
- 27. 2.1999 20:59:22
-
Salampasis, M.; Tait, J.; Bloor, C.: Evaluation of information-seeking performance in hypermedia digital libraries (1998)
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- Abstract
- Discusses current information retrieval methods based on recall (R) and precision (P) for evaluating information retrieval and examines their suitability for evaluating the performance of hypermedia digital libraries. Proposes a new quantitative evaluation methodology, based on the structural analysis of hypermedia networks and the navigational and search state patterns of information seekers. Although the proposed methodology retains some of the characteristics of R and P evaluation, it could be more suitable than them for measuring the performance of information-seeking environments where information seekers can utilize arbitrary mixtures of browsing and query-based searching strategies
-
Ellis, D.: Progress and problems in information retrieval (1996)
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- Date
- 26. 7.2002 20:22:46
- Footnote
- Rez. in: Managing information 3(1996) no.10, S.49 (D. Bawden); Program 32(1998) no.2, S.190-192 (C. Revie)
-
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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- Abstract
- Purpose The purpose of this paper is to propose a method to have more accurate results in comparing performance of the paired information retrieval (IR) systems with reference to the current method, which is based on the mean effectiveness scores of the systems across a set of identified topics/queries. Design/methodology/approach Based on the proposed approach, instead of the classic method of using a set of topic scores, the documents level scores are considered as the evaluation unit. These document scores are the defined document's weight, which play the role of the mean average precision (MAP) score of the systems as a significance test's statics. The experiments were conducted using the TREC 9 Web track collection. Findings The p-values generated through the two types of significance tests, namely the Student's t-test and Mann-Whitney show that by using the document level scores as an evaluation unit, the difference between IR systems is more significant compared with utilizing topic scores. Originality/value Utilizing a suitable test collection is a primary prerequisite for IR systems comparative evaluation. However, in addition to reusable test collections, having an accurate statistical testing is a necessity for these evaluations. The findings of this study will assist IR researchers to evaluate their retrieval systems and algorithms more accurately.
- Date
- 20. 1.2015 18:30:22
-
Reichert, S.; Mayr, P.: Untersuchung von Relevanzeigenschaften in einem kontrollierten Eyetracking-Experiment (2012)
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- Date
- 22. 7.2012 19:25:54
-
¬The Second Text Retrieval Conference : TREC-2 (1995)
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- Content
- Enthält die Beiträge: HARMAN, D.: Overview of the Second Text Retrieval Conference (TREC-2); SPRACK JONES, K.: Reflections on TREC; BUCKLEY, C., J. ALLAN u. G. SALTON: Automatic routing and retrieval using SMART: TREC-2; CALLAN, J.P., W.B. CROFT u. J. BROGLIO: TREC and TIPSTER experiments with INQUERY; ROBERTSON, S.R., S. WALKER u. M.M. HANCOCK-BEAULIEU: Large test collection experiments on an operational, interactive system: OKAPI at TREC; ZOBEL, J., A. MOFFAT, R. WILKINSON u. R. SACKS-DAVIS: Efficient retrieval of partial documents; METTLER, M. u. F. NORDBY: TREC routing experiments with the TRW/Paracel Fast Data Finder; EVANS, D.A. u. R.G. LEFFERTS: CLARIT-TREC experiments; STRZALKOWSKI, T.: Natural language information retrieval; CAID, W.R., S.T. DUMAIS u. S.I. GALLANT: Learned vector-space models for document retrieval; BELKIN, N.J. P. KANTOR, E.A. FOX u. J.A. SHAW: Combining the evidence of multiple query representations for information retrieval
-
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.
-
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
-
Ballerini, J.-P.; Büchel, M.; Domenig, R.; Knaus, D.; Mateev, B.; Mittendorf, E.; Schäuble, P.; Wechsler, M.; Sheridan, P.: SPIDER retrieval system at TREC-5 (1997)
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-
Hawking, D.; Thistlewaite, P.; Bailey, P.: ANU/ACSys TREC-5 experiments : TREC-5 report (1997)
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-
Sheridan, P.; Ballerini, J.P.; Schäuble, P.: Building a large multilingual test collection from comparable news documents (1998)
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-
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
-
Prabha, C.: ¬The large retrieval phenomenon (1991)
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Hersh, W.R.; Over, P.: Interactivity at the Text Retrieval Conference (TREC) (2001)
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Over, P.: ¬The TREC interactive track : an annotated bibliography (2001)
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