Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances

Wong, Wilson

ISBN 10: 1609606256 / ISBN 13: 9781609606251

Published by Information Science Reference, 2011

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides relevant theoretical foundations, and disseminates new research findings and expert views on the remaining challenges in ontology learning. This book is invaluable resource as a library or personal reference for graduate students, researchers, and .

Seller Inventory # 4243232

Bibliographic Details

• Title: Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances
• Publisher: Information Science Reference
• Publication Date: 2011
• Language: English
• ISBN 10: 1609606256
• ISBN 13: 9781609606251
• Binding: Gebunden
• Condition: New

About this title

Synopsis

Ontologies form an indispensable part of the Semantic Web standard stack. While the Semantic Web is still our vision into the future, ontologies have already found a myriad of applications such as document retrieval, image retrieval, agent interoperability and document annotation. Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances provides relevant theoretical foundations, and disseminates new research findings and expert views on the remaining challenges in ontology learning. This book is invaluable resource as a library or personal reference for graduate students, researchers, and industrial practitioners. Readers who are in the process of looking for future research directions, and carving out their own niche area will find this book particularly useful due to the detailed scope and wide coverage of the book, which informs any discussion of artificial intelligence, knowledge acquisition, knowledge representation and reasoning, text mining, information extraction, and ontology learning.

About the Author

Wilson Wong is a Postdoctoral Research Associate at the University of Western Australia (UWA) working on the application of text mining and natural language processing across different domains such as healthcare. Wilson was an Endeavour IPRS Scholar for his PhD study at UWA. His doctoral dissertation investigates the use of Web data for automatically acquiring knowledge from natural language texts across different domains. Wilson also has a BIT (First Class Honours) (Data Communications) degree, and an MSc (Information and Communication Technology) by research degree in the field of natural language processing from Malaysia. Wilson has close to 30 publications in book chapters, reputable conferences (e.g. IJCNLP, IJCAI, PACLING), and high-impact journals (e.g. DMKD, IDA). His areas of interest include text mining, natural language processing, Web technologies, and health informatics.

Wei Liu is an Assistant Professor at the University of Western Australia, and currently the Lab Coordinator for Adaptive System Group. She obtained her PhD from the University of Newcastle on Multi-Agent Belief Revision, Australia in 2003. Her current research interest is on ontology learning to bootstrap agent knowledge base. Dr. Wei Liu's research strength lies in ontology learning and data-driven ontology change. She leads the work on developing automatic and semi-automatic ontology learning system from 2004, which addresses the cold-start issues (labour intensive and time consuming) of manual ontology engineering. The research contributes significantly to the investigation of emergent semantics through text mining. The first paper reporting the techniques and the system modules won one of the best papers in the conference and was invited for journal publication. The techniques developed including co-occurrence analysis to identify taxonomic and non-taxonomic relations, and spreading activation to identify the core, extended, and peripheral concepts. Information network analysis and clustering algorithms are also developed to measure the evolution of an ontology in both temporal and spatial scope.

Mohammed Bennamoun received his PhD from Queen's University, Canada/ Queensland University of Technology (QUT), Australia in the area of Computer Vision. He has been a full Professor and the Head of the School of Computer Science and Software Engineering (CSSE) at the University of Western Australia (UWA) since 2007. Prior to this, he was an Associate Professor at CSSE, a Senior Lecturer at QUT, and a Lecturer at Queen's. He was an Erasmus Mundus Scholar at the University of Edinburgh in 2006. He was also a Visiting Professor at several other institutions including CNRS (Centre National de la Recherche Scientifique), Telecom Lille1, Helsinki University of Technology, University of Bourgogne and University of Paris 13. He is the co-author of the book "Object Recognition: Fundamentals and Case Studies" published by Springer-Verlag. He published over 140 journal and conference publications, and served as a guest editor for several special issues in international journals. His areas of interest include control theory, robotics, obstacle avoidance, object recognition, artificial neural networks, signal/image processing, and computer vision, and lately, in the development of tools for combining text and image analysis.