基于动态演化聚类算法的E-Learning培训搜索研究

摘要

With the development of information society to tell, E-Learning training is more and more applied to various fields of talent training, it can the effect of the users to search the data is related to the long-term development of talents strategy. In this study the brief analysis of the E-Learning training search data structure, using overlapping search module function and index as the objective function with evolutionary clustering algorithm and search data encoding decoding as the foundation, and we build a dynamic network of overlapping for E-Learning training users the dynamic evolution of the clustering algorithm. Finally, experiments show that the proposed dynamic evolutionary clustering algorithm can effectively solve the problem of real-time search user data.%随着信息化社会的高速发展，网络学习（E-Learning）培训越来越的应用到人才培训的各个领域，能否准确地利用用户搜索数据的效果关系到长期人才战略的发展。本研究简要分析了E-Learning培训搜索数据结构，利用重叠搜索模块度函数和指标作为目标函数，以演化聚类算法和搜索数据的编码解码为基础，构建了针对E-Learning培训动态网络重叠用户的动态演化聚类算法。最后实验表明提出的动态演化聚类算法能有效的解决用户实时搜索数据问题。