Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations

Over the past decade tremendous progress has been made in data mining methods like clustering, classification, frequent pattern mining, and so on. Unfortunately, however, the advanced implementations are often not made publicly available, and thus the results cannot be independently verified. We believe that this hampers the rapid advances in the field. With this workshop we intend to promote open source data mining (OSDM) by creating a first meeting place to discuss open source data mining methods.The first steps towards an open source data mining workshop were set in previous years by the Frequent Itemset Mining Implementations workshops (FIMI), which enjoyed a large popularity. The OSDM workshop is held in the same spirit as these earlier workshops, and, in its first edition, the workshop therefore has a special focus on implementations of frequent pattern mining algorithms. It is our hope that in subsequent years the workshop will also focus on open source implementations for other data mining problems like clustering, classification, outlier detection, and so on.Frequent pattern mining is a core field of research in data mining encompassing the discovery of patterns such as itemsets, sequences, trees, graphs, and many other structures. Varied approaches to these problems appear in numerous papers across all data mining conferences. Generally speaking, the problem involves the identification of items, products, symptoms, characteristics, and so forth, that often occur together in a given dataset. As a fundamental operation in data mining, algorithms for FPM can be used as a building block for other, more sophisticated data mining processes. During the last decade, a huge number of algorithms have been developed in order to efficiently solve all kinds of FPM problems. A representative set of such algorithms can now be found in these proceedings, including papers about frequent itemset mining, frequent sequence mining and frequent graph mining.All submissions to this workshop were necessarily accompanied by source code. This source code can also be found on the homepage of the OSDM 2005 workshop:http://osdm.ua.ac.be/All papers were independently reviewed by the members of the program committee.