2008 International Symposiums on Information Processing Research on Automatic Classification for Deep Web Query Interfaces May 23-May 25 ISBN: 978-0-7695-3151-9
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISIP.2008.140
In recent years, the Web is "deepened" rapidly and users have to browse quantities of web sites to access Web databases in a specific domain. So, to build an unified query interface which integrates query interfaces of a domain to access various Web databases at the same time becomes a very important issue. In this paper, the schema characteristics of query interfaces and common attributes in a same domain are firstly analyzed, and it also gives a new representation of query interface, then the definition of "Form term" and "Function term" are proposed ,and a new similarity computing algorithm, literal and semantic based similarity computing (LSSC) is proposed, which is based on the two definitions. Secondly, a clustering algorithm for Deep Web query interfaces is given by combining LSSC and NQ algorithm: LSSC-NQ. Finally, experiments show that this algorithm can give accurate similarity computing, and cluster query interfaces efficiently, reliably and quickly.
Index Terms:
Automatic Classification, Deep Web, Query Interface
Citation:
Peiguang Lin, Yibing Du, Xiaohua Tan, Chao Lv, "Research on Automatic Classification for Deep Web Query Interfaces," isip, pp.313-317, 2008 International Symposiums on Information Processing, 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||