Query Difficulty, Robustness, and Selective Application of Query Expansion

Author:

Amati Giambattista,Carpineto Claudio,Romano Giovanni

Publisher

Springer Berlin Heidelberg

Reference10 articles.

1. Amati, G.: Probability Models for Information Retrieval based on Divergence from Randomness. PhD thesis, Glasgow University (June 2003)

2. Amati, G., Carpineto, C., Romano, G.: FUB at TREC 10 web track: a probabilistic framework for topic relevance term weighting. In: Voorhees, E.M., Harman, D.K. (eds.) Proceedings of the 10th Text Retrieval Conference TREC 2001, Gaithersburg, MD, pp. 182–191. NIST Special Pubblication 500-250 (2002)

3. Amati, G., Van Rijsbergen, C.J.: Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM Transactions on Information Systems (TOIS) 20(4), 357–389 (2002)

4. Carpineto, C., De Mori, R., Romano, G., Bigi, B.: An information theoretic approach to automatic query expansion. ACM Transactions on Information Systems 19(1), 1–27 (2001)

5. Carpineto, C., Romano, G., Giannini, V.: Improving retrieval feedback with multiple termranking function combination. ACM Transactions on Information Systems 20(3), 259–290 (2002)

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