Fuzzy Multi-Criteria Decision Making and Fuzzy Information Gain Based Automotive Recommender System

被引：0

作者：

Gupta, Charu ^{[1
]}

Jain, Amita ^{[2
]}

机构：

[1] Bhagwan Parshuram Inst Technol, Dept Comp Sci & Engn, Delhi, India

[2] Ambedkar Inst Adv Commun Technol & Res, Dept Comp Sci & Engn, Delhi, India

来源：

FUZZY LOGIC IN INTELLIGENT SYSTEM DESIGN: THEORY AND APPLICATIONS | 2018年 / 648卷

关键词：

Automobiles; Information gain; Multi-criteria decision making; Recommender system; Fuzzy TOPSIS; OF-THE-ART;

D O I：

10.1007/978-3-319-67137-6_30

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the current scenario, everyone is very possessive to buy the most suitable automobile for them. The choice to buy an automobile is governed by a large number of features like budget/price, mileage, exteriors, interiors, security features and so on. In this paper an automotive recommender system is proposed which uses the multidimensional criteria to select the best alternatives from a large pool of choices. In this paper, firstly, a feature vector is constructed for each automobile; secondly, a fuzzy information gain is computed for each criteria. This fuzzy gain is used as the weight of the criteria in fuzzy multidimensional decision making. Thus, the choice of automobiles in descending order of preference is recommended.

引用

页码：270 / 277

页数：8

共 22 条

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