Research on the Private Customized Information Retrieval based on Hadoop Cluster
Bo Li, Xiao Zhang, Yan Jingyi · Journal of Physics Conference Series · 2019
Abstract With the development of science and technology, it is no longer a technical difficulty for users to find the answers they need from massive data of information retrieval. At present, with information retrieval methods, the most urgent need is how to find personalized search results that satisfy users and meet their needs. Therefore, private customized information retrieval technology has great research value. This paper builds a Hadoop distributed cluster search engine, improves the PageRank algorithm, adds classified attributes such as user tone, and further classifies and ranks the web pages. At the same time, the C4.5 algorithm is used to classify users, thus it provides private customized search service. Through comparative experimental analysis, it is proved that the improved method proposed in this paper is effective and has profound research value.