A research of the internet based on web information extraction and data fusion
ICWL'10 Proceedings of the 2010 international conference on New horizons in web-based learning
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In this paper we propose a neuro-fuzzy architecture for Web content taxonomy using hybrid of Adaptive Resonance Theory (ART) neural networks and fuzzy logic concept. The search engine called Kavosh1 is equipped with unsupervised neural networks for dynamic data clustering. This model was designed for retrieving images without metadata and in estimating resemblance of multimedia documents; however, in this work only text mining method is implemented. Results show noticeable average precision and recall over search results.