By Haizheng Zhang, Myra Spiliopoulou, Bamshad Mobasher, C. Lee Giles, Andrew McCallum, Olfa Nasraoui, Jaideep Srivastava, John Yen
This e-book constitutes the completely refereed post-workshop court cases of the ninth overseas Workshop on Mining net info, WEBKDD 2007, and the first foreign Workshop on Social community research, SNA-KDD 2007, together held in St. Jose, CA, united states in August 2007 along side the thirteenth ACM SIGKDD overseas convention on wisdom Discovery and knowledge Mining, KDD 2007.
The eight revised complete papers awarded including a close preface went via rounds of reviewing and development and have been rigorously chosen from 23 preliminary submisssions. the improved papers deal with all present matters in internet mining and social community research, together with conventional internet and semantic net purposes, the rising functions of the net as a social medium, in addition to social community modeling and analysis.
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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
We build such a graph in order to ﬁnd all cliques, calculate degree and centrality measures and analyze the social structure of the network. When all the cliques in the graph have been found, we can determine which users are in more cliques, which users are in larger cliques, and which users are in more important cliques. We base it on the assumption that users associated with a larger set and frequency of cliques will then be ranked higher. Finally all of the calculated statistics are normalized and combined, each with an individual contribution to an overall social score with which the users are ultimately ranked.
For few contributors, it was diﬃcult to obtain the organizational hierarchy information. These cases were eliminated during the computation. Index Description of the Feature T1 Total Number of messages for a particular big idea. T2 Total Number of messages which didn’t receive any further response. T3 Total Number of contributors. T4 Forum Number. T5 Total Number of questions asked in that particular idea. T6 Mean of the number of messages for all questions 2 . T7 Standard deviation of the number of messages for all questions 2 .
1 The Innovation Jam Process IBM’s Innovation Jam was designed to take part over two phases. Phase 1 took place July 24-27, 2006 and primarily focused on idea creation and development. Unlike previous IBM Jams where preparation was not necessary, the Jam required familiarization with emerging technologies which were described in online materials made available to participants prior to the event. Individual contributions to the Jam came in the form of “postings,” or messages in reply to other contributors and to questions posed under a moderated topic area.