文章基本信息

标题：Enhanced IR Schemes for Summarizing for Relational Databases
本地全文：下载
作者：K.Chandra Mouli ; G.Aparna
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2012
卷号：3
期号：2
页码：689-693
语种：English
出版社：Ayushmaan Technologies
摘要：Commercial relational database management systems (RDBMSs) generally provide querying capabilities for text attributes that incorporate state-of-the-art information retrieval (IR) relevance ranking strategies, but this search functionality requires that queries specify the exact column or columns against which a given list of keywords is to be matched. This requirement can be cumbersome and inflexible from a user perspective: good answers to a keyword query might need to be “assembled” –in perhaps unforeseen ways– by joining tuples from multiple relations. This observation has motivated recent research on free-form keyword search over RDBMSs. In this paper, we adapt IR-style documentrelevance ranking strategies to the problem of processing freeform keyword queries over RDBMSs. Our query model can handle queries with both AND and OR semantics, and exploits the sophisticated single-column text-search functionality often available in commercial RDBMSs. We develop query-processing strategies that build on a crucial characteristic of IR-style keyword search: only the few most relevant matches –according to some definition of “relevance”– are generally of interest. Consequently, rather than computing all matches for a keyword query, which leads to inefficient executions, our techniques focus on the top-k matches for the query, for moderate values of k.