Learn How To Convert Web Data Into Web Knowledge

This text demonstrates how to extract knowledge by finding meaningful connections among data spread throughout the Web. Readers learn methods and algorithms from the fields of information retrieval, machine learning, and data mining which, when combined, provide a solid framework for mining the Web. The authors walk readers through the algorithms with the aid of examples and exercises.

This text is divided into three parts:

Part One, Web Structure, presents basic concepts and techniques for extracting information from the Web. Readers learn how to collect and index Web documents as well as search and rank Web pages according to their textual content and hyperlink structure.

Part Two, Web Content Management, offers two approaches, clustering and classification, for organizing Web content. For both approaches, the authors set forth specific algorithms that enable readers to convert Web data into knowledge.

Part Three, Web Usage Mining, demonstrates the application of data mining methods to uncover meaningful patterns of Internet usage.

Methods and algorithms are illustrated by simple examples. More than 100 exercises help readers assess their grasp of the material. Further, thirty-four hands-on analysis problems ask readers to use their new data mining expertise to solve real problems, working with large data sets. All the data sets needed for the examples, exercises, and analysis problems are available on the companion Web site.

The extensive use of examples, along with the opportunity to test and apply data mining skills, makes this text ideal for graduate and upper-level undergraduates in computer science andengineering. Web designers and researchers will find that this text gives them a new set of tools to further mine the Web for knowledge and move well beyond the capabilities of standard search engines.

This volume contains the Proceedings of The Third International Conference on Software, Services & Semantic Technologies (S3T) held in Bourgas, Bulgaria on September 1-3, 2011. It is the third S3T conference in a series of annually organized events supported by the F7 EU SISTER Project and hosted by Sofia University. The conference is aimed at providing a forum for researchers and practitioners to discuss the latest developments in the area of Software, Services and Intelligent Content and Semantics. The conference sessions and the contents of this volume are structured according to the conference track themes: Intelligent Content and Semantics (10 papers), Knowledge Management, Business Intelligence and Innovation (4 papers), Software and Services (6 papers), and Technology Enhanced Learning (9 papers). The papers published in this volume cover a wide range of topics related to the track themes. Particular emphasis is placed on applying intelligent semantic technologies in educational and professional environments with papers in the areas of Ontologies and Semantic Web Technologies, Web Data and Knowledge, Social Networks Analysis, Information Extraction and Visualisation, Semantic Search and Retrieval, E-learning, and User Modelling and Personalization.