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A comparison of LSA, wordNet and PMI-IR for predicting user click behavior

, and . Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, page 51--60. New York, NY, USA, ACM, (2005)
DOI: 10.1145/1054972.1054980

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.

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A comparison of LSA, wordNet and PMI-IR for predicting user click behavior

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