Work Weighting Based on User's Browsing History

Work Weighting Based on User's Browsing History

Yutaka Matsuo (National Institute of Advanced Industrial Science & Technology, Japan)
Copyright: © 2005 |Pages: 21
DOI: 10.4018/978-1-59140-567-2.ch009
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This chapter presents discussion of word weighting algorithms in user modelling and adaptive information systems. We specifically address two types of user interest: (1) broad and consistent interest; and (2) narrow, spot interest. A user’s consistent interests can be modelled utilising the user’s information access history; a user’s spot interests can be determined based on that. We developed a word-weighting algorithm to measure the user’s spot interest. The information access history of a user is represented as a set of words. It is considered to be a user model. This method weights words in a document according to their relevancy to the user model. The relevancy is measured by the biases of co-occurrence, called the Interest Relevance Measure, between a word in a document and words in the user model. The future methodology of word weighting is described herein while demonstrating our approach.

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