Keyword Search in DatabasesMorgan & Claypool Publishers, 2010 - 143 pagina's 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 |
Inhoudsopgave
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3 | |
GraphBased Keyword Search | 45 |
Keyword Search in XML Databases | 83 |
Other Topics for Keyword Search on Databases | 115 |
133 | |
Authors Biographies | 143 |
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A{Michelle answer backward search candidate network compute contains keyword data graph DBLP DBLP database defined defined as follows Definition denote Dewey ID Dijkstra’s directed graph Dmax efficiently ELCA elca_canv1 entry enumerates EnumTreePD evaluate final find finding first foreign key references graph G incoming edge InitCNGen innernodes Input iterator join keyword node keyword query keyword search l-keyword large number lca(U lca(v leaf nodes match nodes Michelle MTJNTs number of tuples ObjectRank optimal output P{XML partial tree polynomial delay primary key priority queue Q-subtree query Q r-radius steiner r-radius subgraphs ranking function rdbms relational database Ri{K root node satisfies schema graph score function semantics set of CNs shortest distance shortest path shown in Algorithm shown in Figure SLCA node specifies sql queries stack steiner tree structural subspace subtree rooted super tree supernode text attribute TF-IDF Tmax top-k topk Ttop update XML database XML tree