期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2018
卷号：18
期号：1
页码：87-98
出版社：International Journal of Computer Science and Network Security
摘要：Recommender Systems are an ever trending research that can be applied in various domains. The college recommendation systems for undergraduate students are a challenging area that needs to be explored thoroughly. A college recommendation system provides the means to undergraduate students in their college selection process with a good number of suggestions. In this paper an effective weighted clustering process WCLUSTER is implemented using R-tree data structure. Instead of traditional data clustering approaches, an improved approach using top-k queries is applied for clustering the college data, based on students’ preferences/voting. A new technique was proposed for finding similarity measures between objects by using both values of attributes and their corresponding voting / preferences / ratings for attributes. Traditional methods use distance measures for finding similarity between objects. Proposed method uses voting / preferences / ratings for finding similarity between objects by using top-k query ranking of objects. The preferences were obtained through a well structured questionnaire using which the responses from college students were gathered. Based on the sets of responses as preferences the proposed algorithm was executed. To speed up the query execution process a multidimensional indexing structure called R-Tree was used. Pruning techniques were applied for scalability purpose.
This paper introduced a recommendation system for college/course selection. The experimental results showed that applying WCLUSTER in this domain is superior to traditional and previous approaches.
关键词：;;;; ;;;;;; recommender system; voting; weighted cluster; top-k query; reverse top-k query; multi-dimensional index tree
