Abstract
This article describes a new approach of HTML pages search via Internet, which is based on the semantic understanding of pages content by means of multi-agent technology. Multi-agent text understanding system, which is the basis of the approach, converts an input query and pages, received from conventional search engines, to formalized semantic descriptors, and evaluates similarity of these descriptors. Both text understanding and descriptor comparison algorithms use the knowledge about problem domain, represented in open and easy-to-update form of ontology. The approach developed was applied to the analysis of web-pages related to car industry. As a result a meta-search engine was developed, capable of analyzing pages, retrieved from traditional search engines and sorting pages by their semantic relevance to the user request. In this article one will find description of the system, testing results and future perspectives.
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© 2007 Springer Berlin Heidelberg
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Kanteev, M., Minakov, I., Rzevski, G., Skobelev, P., Volman, S. (2007). Multi-agent Meta-search Engine Based on Domain Ontology. In: Gorodetsky, V., Zhang, C., Skormin, V.A., Cao, L. (eds) Autonomous Intelligent Systems: Multi-Agents and Data Mining. AIS-ADM 2007. Lecture Notes in Computer Science(), vol 4476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72839-9_22
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DOI: https://doi.org/10.1007/978-3-540-72839-9_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72838-2
Online ISBN: 978-3-540-72839-9
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