BibSonomy publications for /user/hotho/dataThu Jan 31 12:01:31 CET 2008LNCSFrom Web to Social Web: Discovering and Deploying User and Content Profiles 47362007web 2007 social myown tm mining data dm This book constitutes the refereed proceedings of the Workshop on Web Mining, WebMine 2006, held in Berlin, Germany, September 18th, 2006. Topics included are data mining based on analysis of bloggers and tagging, web mining, XML mining and further techniques of knowledge discovery. The book is especially valuable for those interested in the aspects of the Social Web (Web 2.0) and its inherent dynamic and diversity of user-generated content.Tue Jan 15 09:55:29 CET 2008Data Warehousing and Knowledge Discovery, Second International Conference, DaWaK 2000, London, UK258-264LNCSEnhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing18742000data preprocessing myown olap intensive 2000 telekom Tue Jun 19 10:57:58 CEST 2007Journal of Computational & Graphical Statistics584-608(25)Building an Effective Representation for Dynamic Networks15September 2006representation toread data network A dynamic network is a special type of network composed of connected transactors which have repeated evolving interaction. Data on large dynamic networks such as telecommunications networks and the Internet are pervasive. However, representing dynamic networks in a manner that is conducive to efficient large-scale analysis is a challenge. In this article, we represent dynamic graphs using a data structure introduced in an earlier article. We advocate their representation because it accounts for the evolution of relationships between transactors through time, mitigates noise at the local transactor level, and allows for the removal of stale relationships. Our work improves on their heuristic arguments by formalizing the representation with three tunable parameters. In doing this, we develop a generic framework for evaluating and tuning any dynamic graph. We show that the storage saving approximations involved in the representation do not affect predictive performance, and typically improve it. We motivate our approach using a fraud detection example from the telecommunications industry, and demonstrate that we can outperform published results on the fraud detection task. In addition, we present a preliminary analysis on Web logs and e-mail networks. Thu Apr 26 14:52:54 CEST 2007Data Preparation for Data Mining1999wg4 preparation kdubiq dm data kdd mining Wed Jan 17 15:56:27 CET 2007SIGIR Forum{T}he {W}ikipedia {X}{M}{L} {C}orpus2006xml data corpus dm wikipedia mining ml Tue Oct 24 14:24:48 CEST 2006Data Engineering Bulletin115-22Hypergraph Based Clustering in High-Dimensional Data Sets: A Summary of Results211998hypergraph toread clustering mining data Fri Jun 23 07:06:19 CEST 2006{UCI} Repository of machine learning databases1998mining machine dm ml learning data dataset uci Mon May 22 13:55:31 CEST 2006SecondPaperbackJuneMorgan Kaufmann Series in Data Management SysData Mining: Practical Machine Learning Tools and Techniques2005mining data ml weka Mon Apr 17 20:02:28 CEST 2006Advances in Knowledge Discovery and Data Mining.1996data dm discovery mining kdd knowledge 2006 lecture definition Tue Apr 04 21:59:56 CEST 2006SIGMOD Record284--93A Brief Survey of Web Data Extraction Tools312002survey extraction ie infromation tools data Sat Feb 11 13:42:47 CET 2006Data Stream Management: Processing High-Speed Data StreamsTemporal Dynamics of On-Line Information Streams2006data topic temporal analysis survey **** trend techniques detection stream Tue Jan 31 15:19:54 CET 2006Journal of Universal Computer Science (J.UCS)7566-590{SEAL-II} --- The Soft Spot between Richly Structured and Unstructured Knowledge72001portal text 2001 mining myown data meta Tue Jan 10 13:54:54 CET 2006Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, San Diego, California, USA, June 9-12, 2003337-348Extracting Structured Data from Web Pages2003structured page extracting data web Sun Jan 08 11:48:04 CET 2006\cite{webkdd99book}92--111Data mining of user navigation patterns2000data navigation user pattern mining Sun Jan 08 11:47:30 CET 2006Journal of Knowledge and Information Systems15--32Data preparation for mining world wide web browsing patterns11999mining data www preparation pattern browsing Sun Jan 08 11:46:14 CET 2006SIGKDD Explorations212--23Web usage mining: discovery and application of usage patterns from web data12000pattern usage discovery mining web data application Sun Jan 08 11:44:48 CET 2006\cite{webkdd99book}163--182Discovery of interesting usage patterns from web data2000web data interesting pattern usage discovery Sun Jan 08 11:42:56 CET 2006San Francisco, LAData Mining. Concepts and Techniques2001concept data mining technique Tue Dec 20 20:21:42 CET 2005Proceedings of the Twenty-third ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, June 14-16, 2004, Paris, France1-12The Lixto Data Extraction Project - Back and Forth between Theory and Practice2004back practice theory data extraction lixto project Tue Dec 20 20:21:42 CET 2005New YorkMining the Web. Transforming Customer Data into Customer Value2001web transforming customer mining data