Semantic Knowledge Management: Integrating Ontology Management, Knowledge Discovery, and Human Language Technologies

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· Springer Science & Business Media
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Despite its explosive growth over the last decade, the Web remains essentially a tool to allow humans to access information. Semantic Web technologies like RDF, OWL and other W3C standards aim to extend the Web’s capability through increased availability of machine-processable information.

Davies, Grobelnik and Mladenic have grouped contributions from renowned researchers into four parts: technology; integration aspects of knowledge management; knowledge discovery and human language technologies; and case studies. Together, they offer a concise vision of semantic knowledge management, ranging from knowledge acquisition to ontology management to knowledge integration, and their applications in domains such as telecommunications, social networks and legal information processing.

This book is an excellent combination of fundamental research, tools and applications in Semantic Web technologies. It serves the fundamental interests of researchers and developers in this field in both academia and industry who need to track Web technology developments and to understand their business implications.

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Dr John Davies leads the Next Generation Web research division at BT. Current interests centre around the application of semantic web and Web 2.0 technology to knowledge management, business intelligence, information integration and service-oriented environments. He is chairman of the European Semantic Technology Conference series (www.estc2007.org) and co-organiser of the ESWC conference series and has written and edited many papers and books in the area of semantic technology and its business applications, web-based information management and knowledge management. He also received the BT Technology Award for Technology Entrepreneurship for his contribution to the creation of Infonic.

Dr. Dunja Mladenic works as a researcher at the Department of Knowledge Technologies of the J. Stefan Institute, Ljubljana, Slovenia since 1992 and is an expert in Machine Learning, Data Mining and Text Mining techniques and their application to real-world problems in different areas such as publishing, medicine, pharmacology, manufacturing, economy. Her current research focuses on data analysis, with particular interest in learning from Text and the Web including personal intelligent agents. She has edited many books and papers in refereed conferences and journals.

Marko Grobelnik is an expert in analysis of large amounts of complex data with the purpose to extract useful knowledge. In particular, his areas of expertise comprise: Data Mining, Text Mining, Information Extraction, Link Analysis, and Data Visualization as well as more integrative areas such as Semantic Web, Knowledge Management and Artificial Intelligence. Apart from research on theoretical aspects of unconventional data analysis techniques, he has valuable experience in the field of practical applications and development of business solutions based on the innovative technologies. He has published many papers in refereed conferences and journals.

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