RNRank: Network-based ranking on relational tuples

Peng Li, Ling Chen, Xue Li, Junhao Wen

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

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.

原文English
主出版物標題Behavior and Social Computing - Int. Workshop on Behavior and Social Informatics, BSI 2013 and Int. Workshop on Behavior and Social Informatics and Computing, BSIC 2013, Revised Selected Papers
發行者Springer Verlag
頁面139-150
頁數12
ISBN(列印)9783319040479
DOIs
出版狀態Published - 2013
事件2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013 - Beijing, China
持續時間: 3 8月 20139 8月 2013

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
8178 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013
國家/地區China
城市Beijing
期間3/08/139/08/13

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