基于免疫克隆选择和语义计算的自适应资源检索算法  

A Resource Retrieval Algorithm with Self-adaptive Feature Based Immune Clonal Selection and Semantic Computing

作　　者：林丽姝[1] 吴明珠[1] 林珍[1] 

机构地区：[1]海南经贸职业技术学院,海南571127

出　　处：《电脑与信息技术》2015年第3期18-20,66,共4页Computer and Information Technology

基　　金：海南省教育科学规划课题(项目编号:QJY125048)

摘　　要：针对传统聚类算法存在的聚类类别数难以确定、易陷入局部极大和无法反映用户反馈的语义信息的问题,提出了一种基于免疫克隆选择和语义计算的自适应资源检索算法。其主要处理环节是使用语义相似度计算公式来计算抗体的免疫优势;引入了自适应优先算子来动态调解聚类类别,检查用户动态反馈的有效性;引入组合因子来增加抗体种群中个体的多样性,以扩大解的搜索范围,避免过早出现早熟现象;实验结果表明,使用该算法比传统聚类算法具有良好的收敛性、稳定性和更高的全局最优。Focused on the problems of strict classification of cluster categories and feedback of semantic information from users in the traditional clustering algorithms, a resource retrieval algorithm with self-adaptive feature based immune clonal selection and semantic computing is proposed in this paper. The main idea of the algorithm is to use Semantic similarity calculation formula to calculate the immunodominance of antibody. The priority operator with self-adaptive feature is introduced to adjust cluster categories automatically and ensure the effectiveness of the dynamic feedback from user. The recombination operator is introduced to increase the diversity of antibody group so as to broaden the search scope of the global optimization solution and avoid early mature phenomenon of the group. The experimental results show that the proposed algorithm is superior to the traditional clustering algorithms in good astringency, stability and overall optimal solutions.

关 键 词：免疫克隆 语义计算 聚类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]