Advances in Data Mining. Applications and Theoretical by Petra Perner

By Petra Perner

This e-book constitutes the refereed lawsuits of the 14th business convention on Advances in info Mining, ICDM 2014, held in St. Petersburg, Russia, in July 2014. The sixteen revised complete papers awarded have been rigorously reviewed and chosen from numerous submissions. the subjects diversity from theoretical facets of information mining to functions of information mining, corresponding to in multimedia information, in advertising, in drugs and agriculture and in technique keep an eye on, and society.

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Extra info for Advances in Data Mining. Applications and Theoretical Aspects: 14th Industrial Conference, ICDM 2014, St. Petersburg, Russia, July 16-20, 2014. Proceedings

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In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 215–224. ACM (2011) 7. : The volume and evolution of web page templates. In: Special Interest Tracks and Posters of the 14th International Conference on World Wide Web, pp. 830–839. ACM (2005) 8. : Entropy-based link analysis for mining web informative structures. In: Proceedings of the Eleventh International Conference on Information and Knowledge Management, pp. 574–581. ACM (2002) 9.

Template detection methods based on RTDM (Restricted Top-Down Mapping) are proposed in [11] [13]. They are motivated by the heuristics that: for each two input pages, if a sub tree that spans from the document root is detected in both pages, then it is regarded as a template. While these methods are efficient, they are of limited use because of the following two reasons: First, in some Web sites, especially article-type sites, many informative contents have almost identical structures, and they tend to be detected as templates in these methods.

For example, a topic related to alcoholic beverages can be broken down into categories that reveal issues brewing, wine making and so on. In the paper we consider the web pages belonging to a number of categories related to the following topics: “adult”, “alcohol”, “gambling”, “tobacco”, “dating”, “drugs”, “hate”, “violence”, “weapon”, “religion”, “occults”. For descriptions of other topics and related categories we used generalized notion of “unknown”. 2 Construction of Base and Combining Classifiers We rely on the formal description of the problem of knowledge extraction from the Web [5] refined by Kleinberg et al.

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