Intelligent Web Content Filtering through Neuro-Fuzzy Approach

This paper presents a brief introduction on web mining techniques. It establishes the need for an intelligent, customised and user-friendly architecture to mine web content in an effective manner. The architecture described in this paper uses co-operative neuro-fuzzy approach to mine and classify web content into five categories using fuzzy user profile and sample training pages. The fuzzy logic component enables vague input to the base neural network and neural network component aids in learning about the user's interest in order to mine the web content effectively. The architecture is generic in nature and can be modified on requirement to mine the content from the given distributed environment.