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A Term Weight Mensuration based on Popularity for Search Query Expansion  

Lee, Jung-Hun (동국대학교 컴퓨터공학과)
Cheon, Suh-Hyun (동국대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.37, no.8, 2010 , pp. 620-628 More about this Journal
Abstract
With the use of the Internet pervasive in everyday life, people are now able to retrieve a lot of information through the web. However, exponential growth in the quantity of information on the web has brought limits to online search engines in their search performance by showing piles and piles of unwanted information. With so much unwanted information, web users nowadays need more time and efforts than in the past to search for needed information. This paper suggests a method of using query expansion in order to quickly bring wanted information to web users. Popularity based Term Weight Mensuration better performance than the TF-IDF and Simple Popularity Term Weight Mensuration to experiments without changes of search subject. When a subject changed during search, Popularity based Term Weight Mensuration's performance change is smaller than others.
Keywords
personalized search; query extraction; clustering; TF-IDF;
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