This volume contains the papers presented at the 7th International Conference on Discovery Science (DS 2004) held at the University of Padova, Padova, Italy, during 2-5 October 2004. The main objective of the discovery science (DS) conference series is to p- videanopenforumforintensivediscussionsandtheexchangeofnewinformation amongresearchersworkingintheareaofdiscoveryscience. Ithasbecomeagood custom over the years that the DS conference is held in parallel with the Int- national Conference on Algorithmic Learning Theory (ALT). This co-location has been valuable for the DS conference in order to enjoy synergy between c- ferences devoted to the same objective of computational discovery but from di?erent aspects. Continuing the good tradition, DS 2004 was co-located with the 15th ALT conference (ALT 2004) and was followed by the 11th Symposium on String Processing and Information Retrieval (SPIRE 2004). The agglome- tion of the three international conferences together with the satellite meetings was called Dialogues 2004, in which we enjoyed fruitful interaction among - searchers and practitioners working in various ?elds of computational discovery. The proceedings of ALT 2004 and SPIRE 2004 were published as volume 3244 of the LNAI series and volume 3246 of the LNCS series, respectively. The DS conference series has been supervised by the international ste- ing committee chaired by Hiroshi Motoda (Osaka University, Japan). The other members are Alberto Apostolico (University of Padova, Italy and Purdue U- versity, USA), Setsuo Arikawa (Kyushu University, Japan), Achim Ho?mann (UNSW, Australia), Klaus P. Jantke (DFKI, Germany), Masahiko Sato (- oto University, Japan), Ayumi Shinohara (Kyushu University, Japan), Carl H.

This book documents the scientific outcome and constitutes the final report of the Japanese reseach project on discovery science. During three years more than 60 scientists participated in the project and developed a wealth of new methods for knowledge discovery and data mining.The 52 revised full papers presented were carefully reviewed and span the whole range of knowledge discovery from logical foundations and inductive reasoning to statistical inference and computational learning. A broad variety of advanced applications are presented including knowledge discovery and data mining in very large databases, knowledge discovery in network environments, text mining, information extraction, rule mining, Web mining, image processing, and pattern recognition.

This volume contains the papers presented at the Second International Conf- ence on Discovery Science (DS 99), held in Tokyo, Japan, December 6-8, 1999. The conference was colocated with the Tenth International Conference on Al- rithmic Learning Theory (ALT 99). This conference was organized as part of the activities of the Discovery S- ence Project sponsored by Grant-in-Aid for Scienti c Research on Priority Area fromthe MinistryofEducation, Science, SportsandCulture (MESSC)ofJapan. This is a three-year project starting from 1998 that aims to (1) develop new methods for knowledge discovery, (2) install network environments for kno- edge discovery, and (3) establish Discovery Science as a new area of computer science. The aim of this conference is to provide an open forum for intensive disc- sions and interchange of new information among researchers working in the new area of Discovery Science. Topics of interest within the scope of this conference include, but are not limited to, the following areas: Logic for/of knowledge discovery, knowledge d- coverybyinferences, knowledgediscoverybylearningalgorithms, knowledged- coverybyheuristicsearch, scienti cdiscovery, knowledgediscoveryindatabases, data mining, knowledge discovery in network environments, inductive logic p- gramming, abductive reasoning, machine learning, constructive programming as discovery, intelligentnetworkagents, knowledgediscoveryfromunstructuredand multimedia data, statistical methods for knowledge discovery, data and kno- edge visualization, knowledge discovery and human interaction, and human f- tors in knowledge discovery. The DS 99 program committee selected 26 papers and 25 posters/demos from 74 submissions. Papers were selected according to their relevance to the conference, accuracy, signi cance, originality, and presentation quali

This volume contains 3 invited papers, 15 regular papers, and 22 poster papers that were selected for presentation at the Third International Conference on Discovery Science (DS 2000), which was held 4-6 December 2000 in Kyoto. The Program Committee selected the contributed papers from 48 submissions. Three distinguished researchers accepted our invitation to present talks: J- frey D. Ullman (Stanford University), Joseph Y. Halpern (Cornell University), and Masami Hagiya (University of Tokyo). The Program Committee would like to thank all those who submitted papers for consideration and the invited speakers. I would like to thank the Program Committee members, the Local Arrangements Committee members, and the Steering Committee members for their splendid and hard work. Finally, special thanks go to the PC Assistant Shoko Suzuki for her assistance in the development of web pages and the preparation of these proceedings. September 2000 Shinichi Morishita Organization Discovery Science 2000 is organized as part of the activities of the Discovery Science Project sponsored by Grant-in-Aid for Scienti?c Research in the Priority Area from the Ministry of Education, Science, Sports and Culture (MESSC) of Japan, in cooperation with the Japanese Society for Arti?cial Intelligence, and with SIG of Data Mining, Japan Society for Software Science and Technology.

This book constitutes the refereed proceedings of the 7th International Workshop on Algorithmic Learning Theory, ALT '96, held in Sydney, Australia, in October 1996.
The 16 revised full papers presented were selected from 41 submissions; also included are eight short papers as well as four full length invited contributions by Ross Quinlan, Takeshi Shinohara, Leslie Valiant, and Paul Vitanyi, and an introduction by the volume editors. The book covers all areas related to algorithmic learning theory, ranging from theoretical foundations of machine learning to applications in several areas.

This volume presents the proceedings of the Fourth International Workshop on Analogical and Inductive Inference (AII '94) and the Fifth International Workshop on Algorithmic Learning Theory (ALT '94), held jointly at Reinhardsbrunn Castle, Germany in October 1994. (In future the AII and ALT workshops will be amalgamated and held under the single title of Algorithmic Learning Theory.)
The book contains revised versions of 45 papers on all current aspects of computational learning theory; in particular, algorithmic learning, machine learning, analogical inference, inductive logic, case-based reasoning, and formal language learning are addressed.