RNRank: Network-Based Ranking on Relational Tuples
Authors: 
Peng Li, Ling Chen, Xue Li, Junhao WenAuthors Info & Claims
Pages 139 - 150
Abstract
Conventional relational top-k queries ignore the inherent referential relationships existing between tuples that can effectively link all tuples of a database together. A relational database can be viewed as a network of tuples connected via foreign keys. With respect to the semantics defined over the foreign keys, the most referenced tuples, therefore, can be regarded as either the most influential, relevant, popular, or authoritative objects stored in a relational database according to its domain semantics. In this paper we propose a novel network-based ranking approach to discover those tuples that are mostly referenced in a relational database as top-k query results. Compared with the conventional relational top-k query processing, our approach can provide information about network structured relational tuples and expand top-k query results as recommendations to users using linkage information in databases. Our experiments on sample relational databases demonstrate the effectiveness and efficiency of our proposed RNRank Relational Network-based Rank approach.
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Index Terms
- RNRank: Network-Based Ranking on Relational Tuples
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Published In
August 2013
263 pages
ISBN:9783319040479
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 03 August 2013
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