Abstract
Search results clustering is useful for clarifying vague queries and in managing the sheer volume of web pages. But these clusters are often incomprehensible to users. In this paper, we propose a new method for producing intuitive clusters that greatly aid in finding desired web search results. By using terms that are both frequently used in queries and found together on web pages to build clusters our method combines the better features of both “computer-oriented clustering” and “human-oriented clustering”. Our evaluation experiments show that this method provides the user with appropriate clusters and clear labels.
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Yasukawa, M., Yokoo, H. (2007). Related Terms Clustering for Enhancing the Comprehensibility of Web Search Results. In: Wagner, R., Revell, N., Pernul, G. (eds) Database and Expert Systems Applications. DEXA 2007. Lecture Notes in Computer Science, vol 4653. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74469-6_36
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DOI: https://doi.org/10.1007/978-3-540-74469-6_36
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