A Semantic Double-Buffer Based Approach to Enhance Semantic Web Search

Abstract

With the development of semantic Web, search efficiency is becoming a challenging issue. To address this problem, we design an approach which mainly has two features. First, we explore potential semantic relationship between different objects and make full use of them to build a semantic buffer on server end, enhancing search speed. Second, we put another relatively small semantic buffer on each client so as to adapt to each individual user's interests, further improving the whole search efficiency and reducing server's load. Through testing on a practical platform, we testified that this semantic double-buffer based search approach can not only effectively reduce user's request response time, but considerably release server's load, bringing a high scalability.