ДОСЛІДЖЕННЯ СУЧАСНИХ ТЕНДЕНЦІЙ ВИКОРИСТАННЯ КЛАСТЕРИЗАЦІЇ ПРИ ВИРІШЕННІ ЗАДАЧІ ПЕРСОНАЛІЗАЦІЇ САЙТУ

Abstract

This paper is devoted is devoted to solving the problems of personalization of users through their queries. The analysis showed that the best method of clustering of search profiles in this caseis CLOPE clustering method. Developed a scalable algorithm, is of great scale and easy implementation complexity Clustering is the analysis of the close search of profiles of users who access the system, thendisplays the previously viewed page based on the search profile of the user. Based on the developed model and the algorithm proposed personalization system that can integrate with web sites toimprove the efficiency of access to relevant user information. An example of personalization based on current needs there is a currently popular recommendation systems that are based on search user profiles. Visitors who will be first to be on the Web site or a web resource of any organization should be judged by the quality and importance of published materials. For large web resources, there is an urgent task of emergency navigation and search user support. It can be solved by the personalization of content based on the needs and behaviors of the end user. When you personalize the web pages will be dynamically change the content of the web resource to the specific needs of the user. As a result, the user will "communicate" with the web page, but the site itself will appeal to anyone who got to the page, not as part of the total mass, and as to the particular person that has their personal interests, personally. To address the issue of clustering was chosen the algorithm of CLOPE, which is suitable for clustering large amounts of data. The algorithm CLOPE, during operation, is maintained a small amount of data for each cluster, with a minimum number of scans. The purpose of this article is to publish the results of the study of modern trends in the use of clustering in solving the problem of personalization.