Published 2007
by Springer in Berlin, New York .
Written in English
Edition Notes
| Other titles | PKDD 2007. |
| Statement | Joost N. Kok ... [et al.] (eds.). |
| Genre | Congresses. |
| Series | Lecture notes in computer science -- 4702., Lecture notes in computer science, LNCS sublibrary |
| Contributions | Kok, Joost N. |
| The Physical Object | |
|---|---|
| Pagination | xxiv, 640 p. : |
| Number of Pages | 640 |
| ID Numbers | |
| Open Library | OL16152226M |
| ISBN 10 | 3540749756 |
| ISBN 10 | 9783540749752 |
The book Knowledge Discovery in Databases, edited by Piatetsky-Shapiro and Frawley [P-SF91], is an early collection of research papers on knowledge discovery from data. The book Advances in Knowledge Discovery and Data Mining, edited by Fayyad, Piatetsky-Shapiro, Smyth, and Uthurusamy [FPSS+96], is a collection of later research results on. The three volume proceedings LNAI – constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD , held in Skopje. Knowledge Discovery in Databases: PKDD 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September , , Proceedings. Series: Lecture Notes in Computer Science, Vol. Subseries: Lecture Notes in . Ulf Brefeld, Élisa Fromont, Andreas Hotho, Arno J. Knobbe, Marloes H. Maathuis, Céline Robardet: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD , Würzburg, Germany, September , , Proceedings, Part I. Lecture Notes in Computer Science , Springer , ISBN
Francesco Bonchi is a senior research scientist at Yahoo! Research in Barcelona, Spain, where he is part of the Barcelona Social Mining Group. He is program co-chair of the upcoming European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD ). ECML-PKDD The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases will take place in Riva del Garda, Italy, during September 19–23, This event is the premier European machine learning and data mining conference and builds upon a very successful series of 26 ECML and 19 PKDD conferences, which have been jointly organized . The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases took place in the Croke Park Conference Centre, Dublin, Ireland during the 10 – 14 September This event is the premier European machine learning and data mining conference and builds upon over 16 years of successful events and conferences held across Europe. This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD , held in Antwerp, Belgium, in September The papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from submissions.
Knowledge Discovery in Databases (KDD) is an automatic, exploratory analysis and modeling of large data repositories. KDD is the organized process of identifying valid, novel, useful, and understandable patterns from large and complex data sets. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization. Figure The Process of Knowledge Discovery in Databases. The process starts with determining the KDD goals, and “ends” with the implementation of the discovered knowledge. Then the loop is closed - the Active Data Mining part starts (which is beyond the scope of this book . This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD , held in Warsaw, Poland, in September , co-located with ECML and PKDD The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data.
