Educational website ranking using fuzzy logic and k-means clustering based hybrid method

被引：8
作者：
Deb K. [1 ]
Banerjee S. [1 ]
Chatterjee R.P. [1 ]
Das A. [2 ]
Bag R. [1 ]
机构：
[1] Department of Computer Science and Engineering, Supreme Knowledge Foundation Group of Institutions, Mankundu, Hooghly, 712139, West Bengal
[2] Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata, 700152, West Bengal
来源：
Ingenierie des Systemes d'Information | 2019年 / 24卷 / 05期
关键词：
Decisive criteria; Fuzzy inference system (FIS); Fuzzy set; Major cluster (MC); Utility value (UV);
D O I：
10.18280/isi.240506
中图分类号：
学科分类号：
摘要：
In the Internet era, it is a huge challenge for users to find suitable and pertinent information out of the huge amount of online data. The challenge is particularly arduous for students searching for education information in a specific domain. To solve the problem, this paper puts forward an educational website ranking method, which applies fuzzy logic and k-means clustering in sequence. First, a fuzzy inference system (FIS) was established based on the fuzzy logic, and used to find the utility value (UV) of an educational website according to the feedback marks of each student. Then, the general utility value (GUV) of each educational website was determined through k-means clustering of all the UVs of that website. Then, the educational websites were ranked by their GUVs. The experimental results show that the proposed method ranks the educational websites clearly and correctly, enabling students to find the desired education information. © 2019 International Information and Engineering Technology Association. All rights reserved.
引用
收藏
页码：497 / 506
页数：9
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