Scalable Internet resource discovery: research problems and approaches
Communications of the ACM
Improved algorithms for topic distillation in a hyperlinked environment
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Data Mining: Introductory and Advanced Topics
Data Mining: Introductory and Advanced Topics
Mining the Web's Link Structure
Computer
Design and evaluation of a multi-agent collaborative Web mining system
Decision Support Systems - Web retrieval and mining
Complementing search engines with online web mining agents
Decision Support Systems - Special issue: Web data mining
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
iJADE Web-Miner: An Intelligent Agent Framework for Internet Shopping
IEEE Transactions on Knowledge and Data Engineering
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With the increasing amount of information available over Internet, there is a need for a more specialized search tool to retrieve quality web pages relevant to the topic of search. The traditional search engines index only the static collections of web and there is a large gap between the current contents of web and the image of WWW stored in search engine databases. An attempt has been made to reduce this shortcoming by mining the web online at query time with adaptive learning multi-agents. The proposed system is scalable in the sense that it downloads several hundreds of relevant web documents per second and is resilient against the system crashes with graceful degradation. It is found that the present technique, as a complementary tool to any of the existing search engines provides a better performance with respect to recency, recall, precision, and coverage.