Kwang-Mo Ahn, Young-Hoon Seo, Heo Jeong, C. Lee, Myung-Gil Jang
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The aim of this paper is to collect relevant keywords from clicklog data including user`s keywords and URLs accessed using them. Our main hyphothesis is that two or more different keywords may be relevant if users access same URLs using them. Also, they should have higher relationship when the more same URLs are accessed using them. To validate our idea, we collect relevant keywords from clicklog data which is offered by a portal site. As a result, our experiment shows 89.32% precision when we define answer set to only semantically same words, and 99.03% when we define answer set to broader sense. Our approach has merits that it is independent on language and collects relevant words from real world data.
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