Research on Automatic Classification for Deep Web Query Interfaces
Peiguang Lin, Yibing Du, Xiaohua Tan, Chao Lv · 2008
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.