STRUDEL: a Web site management system
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An adaptive Web page recommendation service
AGENTS '97 Proceedings of the first international conference on Autonomous agents
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Information Retrieval Systems: Theory and Implementation
Information Retrieval Systems: Theory and Implementation
Modern Information Retrieval
Information Retrieval on the World Wide Web
IEEE Internet Computing
A Query Translation Scheme for Rapid Implementation of Wrappers
DOOD '95 Proceedings of the Fourth International Conference on Deductive and Object-Oriented Databases
WebOQL: Restructuring Documents, Databases, and Webs
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Toward Learning Based Web Query Processing
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
| Hi-index | 0.00 |
Although there are various approaches to facilitate the information search on the Web, most current Web search and query systems only return URLs of relevant pages. Learning-based Web search is invented targeting at processing the URLs to dig out the desired information by utilizing user feedback. However, the involvement of user behavior makes the study of system performance rather complex. In this paper, we introduce the empirical study of a learning-based Web query processing system, named FACT. Four major aspects of user behavior, namely, selection rule, training strategy, training size and training iteration, are considered to show their effects on the learning results. The experimental results are presented, together with analysis for the relationships between user behavior and system performance, which are important for further improvement on learning-based Web search technology.