There are millions of searchable data sources on the Web and to a large extent their contents can only be reached through their own query interfaces. There is an enormous interest in making the data in these sources easily accessible. There are primarily two general approaches to achieve this objective. The first is to surface the contents of these sources from the deep Web and add the contents to the index of regular search engines. The second is to integrate the searching capabilities of these sources and support integrated access to them. In this book, we introduce the state-of-the-art…mehr
There are millions of searchable data sources on the Web and to a large extent their contents can only be reached through their own query interfaces. There is an enormous interest in making the data in these sources easily accessible. There are primarily two general approaches to achieve this objective. The first is to surface the contents of these sources from the deep Web and add the contents to the index of regular search engines. The second is to integrate the searching capabilities of these sources and support integrated access to them. In this book, we introduce the state-of-the-art techniques for extracting, understanding, and integrating the query interfaces of deep Web data sources. These techniques are critical for producing an integrated query interface for each domain. The interface serves as the mediator for searching all data sources in the concerned domain. While query interface integration is only relevant for the deep Web integration approach, the extraction and understanding of query interfaces are critical for both deep Web exploration approaches. This book aims to provide in-depth and comprehensive coverage of the key technologies needed to create high quality integrated query interfaces automatically. The following technical issues are discussed in detail in this book: query interface modeling, query interface extraction, query interface clustering, query interface matching, query interface attribute integration, and query interface integration. Table of Contents: Introduction / Query Interface Representation and Extraction / Query Interface Clustering and Categorization / Query Interface Matching / Query Interface Attribute Integration / Query Interface Integration / Summary and Future Research
Eduard C. Dragut is currently a Postdoctoral Research Associate at Purdue University, Discovery Park, Cyber Center. He completed his Ph.D. degree in Computer Science from University of Illinois at Chicago in July 2010. His Ph.D. research focused on the integration of deep Web sources that provide/sell similar products/services. His research interests include databases, information retrieval, managing unstructured data, information extraction, opinion mining and retrieval, and Web data management. Projects he is actively pursuing include deep Web integration systems, online record linkage and fusion, large-scale entity disambiguation, creation of a sentiment word dictionary, and recently, cyber-infrastructure for scientific research. Weiyi Meng is currently a professor in the Department of Computer Science of the State University of New York at Binghamton. He received his Ph.D. in Computer Science from University of Illinois at Chicago in 1992. In the same year, he joined his current department as a faculty member. He is a co-author of two books "Principles of Database Query Processing for Advanced Applications" and "Advanced Metasearch Engine Technology." He has published over 120 papers. He has served as general chair and program chair of several international conferences and as program committee members of over 50 international conferences. He is on the editorial boards of the World Wide Web Journal, the Frontiers of Computer Science journal, and a member of the Steering Committee of the WAIM conference series. In recent years, his research has focused on metasearch engines, Web data integration, Internet-based Information Retrieval, information extraction, sentiment analysis, and information truthfulness and trustworthiness.He has done pioneering work in large-scale metasearch engines. He was a co-founder of an Internet company (Webscalers) and served as its president. Webscalers developed the world's largest news metasearch engine AllInOneNews. Clement T. Yu isa professor of computer science at the University of Illinois at Chicago. His research interests include multimedia information retrieval, metasearch engine, database management, and applications to healthcare. He has published more than 200 papers in these areas and he is a co-author of two books "Principles of Database Query Processing for Advanced Applications" and "Advanced Metasearch Engine Technology." He served as chairman of the ACM SIGIR and has extensive experience as a consultant in the fields of query processing in distributed and heterogeneous environments, including document retrieval. He was an advisory committee member for the National Science Foundation and was on the editorial boards of IEEE Transactions on Knowledge and Data Engineering, the Journal of Distributed and Parallel Databases, the International Journal of Software Engineering and Knowledge Engineering, and WWW: Internet and Web Information Systems. He also served as the General Chair of the ACM SIGMOD Conference and Program Committee Chair of the ACM SIGIR Conference. He is a co-founder of two Internet companies, Webscalers and PharmIR.
Inhaltsangabe
Introduction.- Query Interface Representation and Extraction.- Query Interface Clustering and Categorization.- Query Interface Matching.- Query Interface Attribute Integration.- Query Interface Integration.- Summary and Future Research.
