WebMate: a personal agent for browsing and searching
AGENTS '98 Proceedings of the second 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
Analysis of a very large web search engine query log
ACM SIGIR Forum
A CORBA extension for intelligent software environments
Advances in Engineering Software - Special issue on large-scale analysis, design and intelligent synthesis environments
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Learning word normalization using word suffix and context from unlabeled data
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
WebSail: From On-line Learning to Web Search
WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 1 - Volume 1
Personalised search on electronic information
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
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Recent increase in interest for information ranking and sharing among users with similar tastes has urged many researches towards improving relevance of search results for reducing costs and offering better quality service to users of Web search engines. Our work has focused largely on the ranking and sharing schemes of retrieved information among heterogeneous sources, whereas Web search engines need to wide crawler with just speed in short time. In this paper, we propose a meta-search agent with a URL filter, a tag-based ranking scheme, and an ontology-based sharing scheme. The meta-search agent uses vector tags to facilitate the definition of informative value and finally the maintenance of shared information. We introduce a concept of vector tag that shows a conceptual distance between retrieval interest and search results. We also compare performance of the proposed system with hyperlink-based methodologies, and analyze the pros and cons of each.