Paper Info
Title
Improve The Effectiveness Of Keyword Search Over Relational Database By Node-Temperature-Based Ant Colony Optimization
Abstract
Keyword search over relational database has been researched a lot. By using simple keywords to search over relational data, ordinary users are not required to learn the difficult structural query language, thus resulting in better user friendliness. Search effectiveness is an important consideration for those solutions to this problem. The available methods adopt static ranking mechanism to ensure that the most relevant answer will be presented first to users. However, they are not able to dynamically optimize the search results according to the time-changing user interest. Here an ant-colony-optimizaton-based algorithm, called ACOKS, is proposed to deal with keyword search problem, in which node-temperature-based optimization is used to achieve dynamic search result optimization by following the track of user behavior. Extensive experimental results show that our methods can achieve better performance than the state-of-the-art methods.
Year
Venue
Keywords
2015
2015 12TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD)
keyword search, ant colony, ACOKS
Field
DocType
Citations 
Query optimization,Web search query,Data mining,Relational database,Computer science,Sargable,Beam search,Search-oriented architecture,Artificial intelligence,Search analytics,Machine learning,Metaheuristic
Conference
0
PageRank 
References 
Authors
0.34
13
3
Name
Order
Citations
PageRank
林子雨112910.80
Yuqian Li200.34
yongxuan lai311220.24