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An Automatic Machine Learning Method for the Study of Keyword Suggestion
Abstract
Keyword suggestion is an automatic machine learning method to suggest relevant keywords to users in order to help users better specify their information needs. In this chapter, the authors adopt two semantic analysis models to build a keyword suggestion system. The suggested keywords returned from the system not only with a certain semantic relationship, but also with a similarity measure. The benefit of the authors’ method is to overcome the problems of synonymy and polysemy over the information retrieval field by using a vector space model. This chapter shows that using multiple semantic analysis techniques to generate relevant keywords can give significant performance gains.
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