Contribution to topic identification by using word similarity

@inproceedings{Brun2002ContributionTT,
  title={Contribution to topic identification by using word similarity},
  author={Armelle Brun and Kamel Sma{\"i}li and Jean Paul Haton},
  booktitle={INTERSPEECH},
  year={2002}
}
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 wellknown 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… CONTINUE READING

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