Contribution to Topic Identification by Using Word Similarity - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2002

Contribution to Topic Identification by Using Word Similarity

Abstract

In this paper, a new topic identification method, WSIM, is investigated. It exploits the similarity between words and topics. This measure is a function of the similarity between words, based on the mutual information. The performance of WSIM is compared to the cache model and to the well-known SVM classifier. Their behavior is also studied in terms of recall and precision, according to the training size. Performance of WSIM reaches 82.4 % correct topic identification. It outperforms SVM (76.2%) and has a comparable performance with the cache model (82.0\%).
Not file

Dates and versions

inria-00100947 , version 1 (26-09-2006)

Identifiers

  • HAL Id : inria-00100947 , version 1

Cite

Armelle Brun, Kamel Smaïli, Jean-Paul Haton. Contribution to Topic Identification by Using Word Similarity. 7th International Conference on Spoken Language Processing - ICSLP'2002, Sep 2002, Denver, Colorado, USA, 4 p. ⟨inria-00100947⟩
86 View
0 Download

Share

Gmail Facebook Twitter LinkedIn More