Keyword Search in Databases
jun 2022. · Springer Nature
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143
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O ovoj e-knjizi
It has become highly desirable to provide users with flexible ways to query/search information over databases as simple as keyword search like Google search. This book surveys the recent developments on keyword search over databases, and focuses on finding structural information among objects in a database using a set of keywords. Such structural information to be returned can be either trees or subgraphs representing how the objects, that contain the required keywords, are interconnected in a relational database or in an XML database. The structural keyword search is completely different from finding documents that contain all the user-given keywords. The former focuses on the interconnected object structures, whereas the latter focuses on the object content. The book is organized as follows. In Chapter 1, we highlight the main research issues on the structural keyword search in different contexts. In Chapter 2, we focus on supporting structural keyword search in a relational database management system using the SQL query language. We concentrate on how to generate a set of SQL queries that can find all the structural information among records in a relational database completely, and how to evaluate the generated set of SQL queries efficiently. In Chapter 3, we discuss graph algorithms for structural keyword search by treating an entire relational database as a large data graph. In Chapter 4, we discuss structural keyword search in a large tree-structured XML database. In Chapter 5, we highlight several interesting research issues regarding keyword search on databases. The book can be used as either an extended survey for people who are interested in the structural keyword search or a reference book for a postgraduate course on the related topics. Table of Contents: Introduction / Schema-Based Keyword Search on Relational Databases / Graph-Based Keyword Search / Keyword Search in XML Databases / Other Topics for Keyword Search on Databases
O autoru
Jeffrey Xu Yu received his B.E., M.E., and Ph.D. in computer science, from the University of Tsukuba, Japan, in 1985, 1987 and 1990, respectively. Dr. Yu held teaching positions in the Institute of Information Sciences and Electronics, University ofTsukuba, Japan, and the Department of Com[1]puter Science,The Australian National University. Currently, he is a Professor in the Department of Systems Engineering and Engineering Management, the Chinese University of Hong Kong. Dr. Yu served as an associate editor of IEEE Transactions on Knowledge and Data Engineering, and is serving as a VLDB Journal editorial board member, and an Information Director of ACM Special Interest Group on Management of Data. His current main research interest includes keyword search in relational databases, graph database, graph mining, XML database, and Web-technology. He has published over 190 papers including papers published in reputed journals and major international conferences. Lu Qin received the B.S. degree from Renmin University of China in 2006. He is currently a PhD candidate in the Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong. His research interests include keyword search in relational databases, keyword search in large graphs and multi-query optimization in relational database management systems. Lijun Chang received the B.S. degree from Renmin University of China in 2007. He is currently a PhD candidate in the Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong. His research interests include uncertain data man[1]agement and keyword search in databases
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