DocumentCode
2301911
Title
Selection of Deep Web Database Based on Retrieval Performance
Author
Li, Weijing ; Yuan, Fang ; Zhang, Ming
Author_Institution
Key Lab. in Machine Learning & Comput. Intell., Hebei Univ., Baoding, China
Volume
3
fYear
2010
fDate
6-7 March 2010
Firstpage
72
Lastpage
75
Abstract
A mass of high-quality information included in Deep Web can be accessed, which is still growing rapidly with the rapid development of the World Wide Web. Therefore it becomes more and more important to find the Web databases which are most relevant to the user queries. In this paper we propose a selection method of Web database based on retrieval performance. This method can fix the topic based on website characteristics and then classify the websites. Finally it decides which Web database can be chosen based on the retrieval performance. This method can not only accurately select the Web databases which satisfy the user queries but also improve the speed of the database query and the quality of retrieval.
Keywords
Web sites; information retrieval; query languages; query processing; World Wide Web; database query; deep Web database; retrieval performance; user queries; website characteristics; Books; Computer science; Computer science education; Content based retrieval; Costs; Databases; Educational technology; Engines; Information retrieval; Machine learning; Web database selection; component; retrieval performance; topic;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Electronic_ISBN
978-1-4244-6389-3
Type
conf
DOI
10.1109/ETCS.2010.613
Filename
5459955
Link To Document