@inproceedings{Kaur:2005:CLW:1054972.1054980,
  abstract = {A predictive tool to simulate human visual search behavior would help interface designers inform and validate their design. Such a tool would benefit from a semantic component that would help predict search behavior even in the absence of exact textual matches between goal and target. This paper discusses a comparison of three semantic systems-LSA, WordNet and PMI-IR-to evaluate their performance in predicting the link that people would select given an information goal and a webpage. PMI-IR best predicted human performance as observed in a user study.},
  acmid = {1054980},
  address = {New York, NY, USA},
  author = {Kaur, Ishwinder and Hornof, Anthony J.},
  booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
  doi = {10.1145/1054972.1054980},
  interhash = {ea35528c6c3ea3ca64cbbd6c6ae631ae},
  intrahash = {f8c070cb738ea82a40838b1eb8257e31},
  isbn = {1-58113-998-5},
  location = {Portland, Oregon, USA},
  numpages = {10},
  pages = {51--60},
  publisher = {ACM},
  series = {CHI '05},
  title = {A comparison of LSA, wordNet and PMI-IR for predicting user click behavior},
  url = {http://doi.acm.org/10.1145/1054972.1054980},
  year = 2005
}