Entropy measurement and algorithm for Semantic-Synaptic web mining

Semantic-Synaptic Web mining [1] aims to integrate the best idea from the semantic Web and synaptic Web with Web mining at low entropy. Semantic entropy can help researchers to decide not only how to work with words, but which words to work with. Many researchers are struggling to upgrade the result of Web mining by capitalizing semantic structure of the Web so that one can get the relevant and efficient information from the Web, but efficient and relevant information extracting from the Web still faces a big challenge. Semantic-Synaptic Web mining present a novel mining technique which interlinks the Web of data to different data sources available on the Web which have low entropy, so that one can find out the most relevant and accurate information on the Web. This paper proposes an algorithm for semantic-synaptic Web mining and presents a method for measuring the entropy of Web pages using information content.