Incorporating quality metrics in centralized/distributed information retrieval on the World Wide Web
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Personal ontologies for web navigation
Proceedings of the ninth international conference on Information and knowledge management
Towards context-based search engine selection
Proceedings of the 6th international conference on Intelligent user interfaces
Agents teaching agents to share meaning
Proceedings of the fifth international conference on Autonomous agents
Ontology Based Personalized Search
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Learning to Share Meaning in a Multi-Agent System
Autonomous Agents and Multi-Agent Systems
Ontology-based personalized search and browsing
Web Intelligence and Agent Systems
BDEI: Biodiversity Information Organization using Taxonomy (BIOT)
dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
Using evidence based content trust model for spam detection
Expert Systems with Applications: An International Journal
A framework towards a multi-modal fingerprinting scheme for multimedia assets
International Journal of Business Information Systems
SVM based automatic user profile construction for personalized search
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Roles of agents in data-intensive web sites
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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Centralized search process requires that the whole collection reside at a single site. This imposes a burden on both the system storage of the site and the network traffic near the site. It thus comes to require the search process to be distributed. Recently, more and more Web sites provide the ability to search their local collection of Web pages. Query brokering systems are used to direct queries to the promising sites and merge the results from these sites. Creation of meta-information of the sites plays an important role in such systems. In this article, we introduce an ontology-based web site mapping method used to produce conceptual meta-information, the Vector Space approach, and present a serial of experiments comparing it with Naïve-Bayes approach. We found that the Vector Space approach produces better accuracy in ontology-based web site mapping.