Work Weighting Based on User's Browsing History

Abstract

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.