Semantic-Synaptic Web Mining: A Novel Model for Improving the Web Mining

Web mining is the application of data mining technique to automatically discover and gathered information from web documents and services which can be in structured, unstructured or semi-structured form. It is used to understand user behaviour, evaluate the effectiveness of a particular web and find out the relevant and efficient results from the web. Accuracy and relevance of information extracting from the web is the most significant issue of concern for the realization of web mining. The idea is to improve the accuracy and relevance of information extracting from the web. This paper proposes a novel model for improving the web mining, we hypothesize that web mining is Semantic-Synaptic web mining. Semantic-Synaptic web Mining interlinks the web of data to different data sources at low entropy (Information Theory). This paper combines the best ideas from the semantic web and synaptic web at low entropy and constructs the architecture of Semantic-Synaptic web mining.