@article{1070,
  author = {Imen Akermi, Rim Faiz},
  title = {A Novel Method for Word-Pair Similarity Computing},
  journal = {International Journal of Computational Linguistics Research},
  year = {2012},
  volume = {3},
  number = {4},
  doi = {},
  url = {http://www.dline.info/jcl/fulltext/v3n4/1.pdf},
  abstract = {Semantic similarity between words is fundamental to various fields such as Cognitive Science, Artificial Intelligence, Natural Language Processing and Information Retrieval. According to Baeza-Yates and Neto [2] an Information Retrieval system “should provide the user with easy access to the information in which he is interested”. Therefore, in this domain, relying on a robust semantic similarity measure is crucial for automatic query suggestion and expansion process. In this same context, we propose a method that uses on one hand, an online English dictionary provided by the Semantic Atlas project of the French National Centre for Scientific Research (CNRS) and on the other hand, a page counts based metric returned by a social website.},
}