Semantic Map Based Web Search Result Visualization

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Semantic Map Based Web Search Result Visualization

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dc.contributor.author Hamdi, Mohamed Salah
dc.date.accessioned 2009-12-30T05:44:44Z
dc.date.available 2009-12-30T05:44:44Z
dc.date.issued 2007-07-04
dc.identifier.uri http://dx.doi.org/10.1109/IV.2007.99
dc.identifier.uri http://hdl.handle.net/10576/10574
dc.description.abstract The problem of information overload has become more pressing with the emergence of the increasingly more popular Internet services. The main information retrieval mechanisms provided by the prevailing Internet Web software are based on either keyword search (e.g., Google and Yahoo) or hypertext browsing (e.g., Internet Explorer and Netscape). The research presented in this paper is aimed at providing an alternative concept-based categorization and search capability based on a combination of meta-search and self-organizing maps. Kohonen's self-organizing map is very well known as a clustering and dimension reduction tool. Clustering can be used for categorization of search results. Dimension reduction can be used for visualization and for reducing information in order to ease search. en_US
dc.language.iso en en_US
dc.subject Semantic Map en_US
dc.subject Web Search en_US
dc.title Semantic Map Based Web Search Result Visualization en_US
dc.type Article en_US

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