An Aggregation Cache Replacement Algorithm Based on Ontology Clustering

作     者：ZHU Jiang SHEN Qingguo TANG Tang LI Yongqiang 

作者机构：Institute of Communications Engineering PLAUniversity of Science and Technology Nanjing. 210007Jiangsu China 

出 版 物：《Wuhan University Journal of Natural Sciences》 (武汉大学学报（自然科学英文版）)

年 卷 期：2006年第11卷第5期

页      面：1141-1146页

学科分类：08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 

基　　金：Supported by the National Natural Science Foun-dation of China (60472050) 

主　　题：ontology similarity replacement algorithm content adaptation semantic Web 

摘      要：This paper describes the theory, implementation, and experimental evaluation of an Aggregation Cache Replacement （ ACR ） algorithm. By considering application background, carefully choosing weight values, using a special formula to calculate the similarity, and clustering ontologies by similarity for getting more embedded deep relations, ACR combines the ontology similarity with the value of object and decides which object is to be replaced. We demonstrate the usefulness of ACR through experiments. （a） It is found that the aggregation tree is created wholly differently according to the application cases. Therefore, clustering can direct the content adaptation more accurately according to the user perception and can satisfy the user with different preferences. （b） After comparing this new method with widely-used algorithm Last-Recently-Used （LRU） and First-in-First-out （FIFO） method, it is found that ACR outperforms the later two in accuracy and usability. （c） It has a better semantic explanation and makes adaptation more personalized and more precise.