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Data mining

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Data mining

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The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qua- ?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall. We thank all involved for all the e?ort with reviewing and selection of papers. Besidesthecoretechnicalprogram,ECMLandPKDDhad6invitedspeakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.

Data mining

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This book offers a balanced view between a basic introduction of Social Network Analysis (SNA) in its methods and application, and advanced topics of data mining techniques and the subsequent SNA analyses. The book stands out as uniquely important contribution to the SNA field because it moves beyond the stage of basic SNA methods. It describes data mining techniques, introducing an online discourse collection platform, ICAS, which is developed by an interdisciplinary team involving Sociologists and Computer Engineer teams with supports of NSF funds. Targeted audiences of this book are students and scholars interested in using SNA techniques to advance their analytics of their respective research areas. This book provides particular utilities to students at the beginner stage of learning SNA basics, and those in their intermediary careers looking to advance their knowledges of what SNA has to offer. The unique features of this book lie in its descriptions of data mining techniques, data processing, and data analytics. The discussions of an online discourse network platform and data processing capabilities present tremendous benefits to those who aspire to mine the massive data of online social networking.

Data mining. --- Data Mining and Knowledge Discovery.

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Mathematical statistics --- Data mining