Developing an adaptive search engine for e-commerce using a Web mining approach

Abstract

Discusses current work using an adaptive learning algorithm to dynamically create the content of an e-commerce search engine so that the implicit knowledge extracted by the Web text mining module can be provided in the B2B (business-to-business) portal. In this paper, we develop an algorithmic approach for automatically discovering implicit customer knowledge from the Internet by means of a Web mining method. Using a variation of the automatic thesaurus generation techniques, namely the self-organizing map (SOM) neural net, we have conducted several experiments in a specific domain in which we created a functional thesaurus of numerous supplier- and product-specific terms. Further, we applied such a thesaurus in a topic hierarchy-based text database, as an organized text source of a search engine for a novel B2B e-commerce portal.