Download Active mining: new directions of data mining by Hiroshi Motoda PDF

By Hiroshi Motoda

ISBN-10: 158603264X

ISBN-13: 9781586032647

ISBN-10: 4274905217

ISBN-13: 9784274905216

The necessity for amassing proper info assets, mining invaluable wisdom from various sorts of facts resources and quickly reacting to state of affairs switch is ever expanding. lively mining is a suite of actions every one fixing part of this want, yet jointly attaining the mining aim in the course of the spiral impact of those interleaving 3 steps. This ebook is a joint attempt from major and energetic researchers in Japan with a subject approximately lively mining and a well timed file at the vanguard of information assortment, user-centered mining and consumer interaction/reaction. It bargains a modern review of recent suggestions with real-world functions, stocks hard-learned reviews, and sheds gentle on destiny improvement of energetic mining.

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If notification is not necessary, do nothing and go to 1. ii. If plural regions are matched, indicate a user a Web page in which the regions are highlighted arid he/she evaluates it. If the update is correct. go to 2. Otherwise go to 1. iii. If no matched region, go to 1. Fig. 3 shows interface of PUM. The window consists of three sub-windows: a Web browser window, an URL window and a training example window. A Web browser window (lower right in Fig. 3) shows a Web page in the same way to a Web browser and a user can easily indicate a region by highlighting it using a mouse.

Pages 301 307, 1997. [3] S. Goto and H. Nojima. Analysis of the three-layered structure of information flow in human societies. Journal of Japanese Society for Artificial Intelligence (in Japanese). 8(3):348 356. 1993. This paper also appears in Artifical Intelligence. edU/~ kraek/. [5] M. Lea. Contexts of computer-mediated communication. Harvester Wheatsheaf, pages 30 65. 1992. 20 M. Numao et al. / Data Mining on the WAVEs [6] Pattie Maes. Agents that reduce work and information. CACM. 37(7):30– 40.

The method extracts the keywords that can be used as the landmarks of the major topics in a document set. while the document clustering is performed with the keywords. The proposed method employs the immune network model to calculate the activation values of keywords. The questionnaires are performed to compare the clusters generated by the proposed method and those generated by k-means clustering method, of which the results show that the proposed method can get better results in terms of the coherence than k-means.

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Active mining: new directions of data mining by Hiroshi Motoda


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