Advances in Web Mining and Web Usage Analysis: 9th by Haizheng Zhang, Myra Spiliopoulou, Bamshad Mobasher, C. Lee

By Haizheng Zhang, Myra Spiliopoulou, Bamshad Mobasher, C. Lee Giles, Andrew McCallum, Olfa Nasraoui, Jaideep Srivastava, John Yen

This booklet constitutes the completely refereed post-workshop lawsuits of the ninth overseas Workshop on Mining internet facts, 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 information Mining, KDD 2007.

The eight revised complete papers provided 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 net mining and social community research, together with conventional net and semantic net functions, the rising purposes of the net as a social medium, in addition to social community modeling and analysis.

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Extra resources for Advances in Web Mining and Web Usage Analysis: 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop

Example text

Therefore when we cluster the threads from Phase 1 and Phase 2, an optimal case is that we can find three types of clusters: (1) the clusters that mostly consist of threads in Phase 1 (2) those mostly composed of threads in Phase 2; and (3) the clusters with the threads in both phases, which help us examine if they are the potential finalists for funding. Several clustering algorithms have been investigated, including K-means, hierarchical clustering, bisecting K-means and so on [10]. The results from different clustering algorithms are similar and therefore we only discuss the ones using the completelinkage agglomerate clustering algorithm.

Percentage of messages in each forum for Phase 1 and Phase 2 Percentage Percentage of Contributors 50 45 40 35 30 25 20 15 10 5 0 Phase 1 Phase 2 1 2 3 4 5 6 7 8 9 10 Number of Responses Fig. 3. Percentage of contributors who responded more than 1-20 times during Phase 1 and Phase 2 1 and 3640 in Phase 2, it is interesting to note that these percentages are very similar for both phases. For example, percentage of contributors who responded at least 3 times is 18% for Phase 1 and 16% for Phase 2.

The three largest threads were selected for analysis, with the first discussing “Sustainable energy systems”, the other on “Digital entertainment” and the third on “Global travel” with 622, 405 and 776 posts respectively. To determine whether a series of posts have a focused discussion or not, we compare the content similarity as well as the number of unique contributors. We preprocess the texts in each post using the bag-of-words representation described before, and then calculate the averaged cosine similarity between 10 adjacent posts in a time-based consecutive order.

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