Abstract
Since 1995, we have been developing web search engine “Mondou” using data mining techniques (http://www.kuamp.kyoto-u.ac.jp/labs/ infocom/mondou/index_e.html) in order to discover the helpful information for web search operations. In our previous works, we focus on the computing cost to derive associative keywords, we propose the method to determine system parameters, such as Minsup and Minconf threshold values. Moreover we evaluate the ROC performance of derived keywords by weighted association algorithms. In this paper, we try to implement two kinds of Java applets in our Mondou system, such as ROC graph for selecting associative keywords and documents clustering. This visual interface shows characteristics of associative rules on the ROC graph with the Minsup values. It also provides the function of document clustering in order to visualize retrieved documents.
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Kawano, H., Kawahara, M. (2000). Mondou: Information Navigator with Visual Interface. In: Kambayashi, Y., Mohania, M., Tjoa, A.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2000. Lecture Notes in Computer Science, vol 1874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44466-1_43
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DOI: https://doi.org/10.1007/3-540-44466-1_43
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