Download Advances in Web Mining and Web Usage Analysis: 9th by Miklós Kurucz, András A. Benczúr (auth.), Haizheng Zhang, PDF

By Miklós Kurucz, András A. Benczúr (auth.), Haizheng Zhang, Myra Spiliopoulou, Bamshad Mobasher, C. Lee Giles, Andrew McCallum, Olfa Nasraoui, Jaideep Srivastava, John Yen (eds.)

This e-book constitutes the completely refereed post-workshop lawsuits of the ninth foreign Workshop on Mining net info, WEBKDD 2007, and the first overseas Workshop on Social community research, SNA-KDD 2007, together held in St. Jose, CA, united states in August 2007 along with the thirteenth ACM SIGKDD foreign convention on wisdom Discovery and knowledge Mining, KDD 2007.

The eight revised complete papers offered including an in depth preface went via rounds of reviewing and development and have been conscientiously chosen from 23 preliminary submisssions. the improved papers deal with all present matters in internet mining and social community research, together with conventional net and semantic net functions, the rising functions of the net as a social medium, in addition to social community modeling and analysis.

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Read or Download Advances in Web Mining and Web Usage Analysis: 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop on Social Networks Analysis, SNA-KDD 2007, San Jose, CA, USA, August 12-15, 2007. Revised Papers PDF

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Additional info for Advances in Web Mining and Web Usage Analysis: 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop on Social Networks Analysis, SNA-KDD 2007, San Jose, CA, USA, August 12-15, 2007. Revised Papers

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30 5 W. Gryc et al. Unsupervised Content Analysis The high-level challenge of our analysis of the Innovation Jam data is to identify the keys to success of such an endeavor, in particular, what are the characteristics of discussion threads that lead to innovative and promising ideas? The major differences between the Jam data and a typical forum are: a) the topics are more concentrated and controlled; b) the contributors are mostly from one organization, and therefore share similar concepts on basic values and what are the “great” ideas; c) the discussion time spans a shorter time.

A group of conversationalists can be characterized by a large number of posts and replies to each other. While the social network analysis of Innovation Jam participants is beyond the scope of the paper, it is important to note that the social structure of the Jam has an effect on its outcomes. Newsgroups or forums can develop their own internal social structures. Groups can also be seen as those that develop unique linguistic or social traits [6]. For example, groups may begin to use new words or acronyms, lending support to the idea that predicting convergence in discussions or brainstorms is possible.

This multi-stage format provides a rich set of data for investigation of how ideas evolve via moderated discussion. Of particular interest is whether we can detect characteristics of those discussion threads that can be linked to an idea ultimately being selected as a promising initiative. To the extent that selected ideas reflect some indication of “innovation,” we have some basis for examining which aspects of a discussion thread may lead to innovation. This paper summarizes our efforts to characterize successful threads in terms of features drawn from both the thread content as well as information like the organizational divergsity of the participants in such threads.

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