BM25-CTF: Improving TF and IDF factors in BM25 by using collection term frequencies

Author:

Jimenez Sergio1,Cucerzan Silviu-Petru2,Gonzalez Fabio A.3,Gelbukh Alexander4,Dueñas George1

Affiliation:

1. Instituto Caro y Cuervo, Calle 10 #4-69, Bogotá, D.C., Colombia

2. Microsoft Research, One Microsoft Way, Redmond, WA, US

3. Universidad Nacional de Colombia, Ciudad Universitaria, Bogotá, D.C., Colombia

4. CIC, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz, 07738, Mexico City, Mexico

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference36 articles.

1. An information-theoretic perspective of tf-idf measures;Aizawa;Inf Process Manag,2003

2. Probabilistic models of information retrieval based on measuring the divergence from randomness;Amati;ACM Trans Inf Syst,2002

3. Büttcher S. and Charles L.A. , Clarke, Efficiency vs, effectiveness in terabyte-scale information retrieval, In Proceedings of TREC 2005 2005.

4. Inverse Document Frequency (IDF): A Measure of Deviations from Poisson

5. Evolving local and global weighting schemes in information retrieval;Cummins;Information Retrieval,2006

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