Integrating word relationships into language models

  • Authors:
  • Guihong Cao;Jian-Yun Nie;Jing Bai

  • Affiliations:
  • Université de Montréal, Montréal, Québec, Canada;Université de Montréal, Montréal, Québec, Canada;Université de Montréal, Montréal, Québec, Canada

  • Venue:
  • Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2005

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Abstract

In this paper, we propose a novel dependency language modeling approach for information retrieval. The approach extends the existing language modeling approach by relaxing the independence assumption. Our goal is to build a language model in which various word relationships can be integrated. In this work, we integrate two types of relationship extracted from WordNet and co-occurrence relationships respectively. The integrated model has been tested on several TREC collections. The results show that our model achieves substantial and significant improvements with respect to the models without these relationships. These results clearly show the benefit of integrating word relationships into language models for IR.