Sub-Component Optimization for Web-Dist Measurement

In recent years, machine learning techniques are taken into account in more and more Web-based systems in order to design intelligent mechanisms for organizing, indexing, and retrieving Web content, and it is necessary for researches and applications to calculate persuasive distance of Web pages. General methodologies are fit for extracting the differences between HTML documents of Web pages; however, it cannot be used to tell the actual distance, between the content of Web pages and the facade displayed in Internet explorers. Previously, content distance, style distance, and hybrid distance have been proposed to make measurement result more practical. In this paper, in order to make more effective description on Web-dist functions, a sub-component based optimization methodology is proposed, and the efficiency is proved through some practical applications