Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.

The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.

Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.

The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.

This book constitutes the thoroughly refereed and extended post-proceedings of the joint European Web Mining Forum, EWMF 2005, and the International Workshop on Knowledge Discovery and Ontologies, KDO 2005, held in association with ECML/PKDD in Porto, Portugal in October 2005. The 10 revised full papers presented together with one invited paper and one particularly fitting contribution from KDO 2004 were carefully selected for inclusion in the book.

In the last years, research on Web mining has reached maturity and has broadened in scope. Two different but interrelated research threads have emerged, based on the dual nature of the Web: - The Web is a practically in?nite collection of documents: The acquisition and - ploitation of information from these documents asks for intelligent techniques for information categorization, extraction and search, as well as for adaptivity to the interests and background of the organization or person that looks for information. - The Web is a venue for doing business electronically: It is a venue for interaction, information acquisition and service exploitation used by public authorities, n- governmental organizations, communities of interest and private persons. When observed as a venue for the achievement of business goals, a Web presence should be aligned to the objectives of its owner and the requirements of its users. This raises the demand for understandingWeb usage, combining it with other sources of knowledge inside an organization, and deriving lines of action. ThebirthoftheSemanticWebatthebeginningofthedecadeledtoacoercionofthetwo threadsintwoaspects: (i)theextractionofsemanticsfromtheWebtobuildtheSemantic Web;and(ii)theexploitationofthesesemanticstobettersupportinformationacquisition and to enhance the interaction for business and non-business purposes. Semantic Web mining encompasses both aspects from the viewpoint of knowledge discovery

This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997.
This volume presents 26 revised full papers selected from a total of 73 submissions. Also included are an abstract and two papers corresponding to the invited talks as well as descriptions from four satellite workshops. The volume covers the whole spectrum of current machine learning issues.