Affiliation:
1. National Dong Hwa University, Taiwan
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.
Reference53 articles.
1. Abhishek, V., & Hosanagar, K. (2007a). Keyword generation for search engine advertising using semantic similarity between terms. Paper presented at the Ninth International Conference on Electronic Commerce.
2. Abhishek, V., & Hosanagar, K. (2007b). Keyword generation for search engine advertising using semantic similarity between terms. Paper presented at the Ninth International Conference on Electronic Commerce.
3. AOL. (2006). AOL search data. Retrieved December 6, 2009, from http://www.gregsadetsky.com/aol-data/
4. AOL. (2008). AOL search - 2008 year end hot searches. Retrieved December 6, 2009, from http://about-search.aol.com/hotsearches2008/index.html