Comparing product specifications to solve the Cold Start problem in a recommender system

被引：1

作者：

Aciar, Silvana ^{[1
]}

Aciar, Gabriela ^{[1
]}

Zhang, Debbie ^{[2
]}

机构：

[1] Univ Nacl San Juan, Inst Informat, Rivadavia, San Juan Provin, Argentina

[2] Univ Technol Sydney, Fac IT, Sydney, NSW, Australia

来源：

PROCEEDINGS OF THE 2016 XLII LATIN AMERICAN COMPUTING CONFERENCE (CLEI) | 2016年

关键词：

Text Mining; Recommender Systems; Opinions; User's Interactions;

D O I：

10.1109/CLEI.2016.7833354

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Recommender systems are widely used applications to solve the problems of information overload, usually on websites. A well-known problem of recommender systems is the problem of cold start, which is caused by the lack of data. A recommendation system can only produce good recommendations after it has accumulated enough data The problem becomes even more challenging when the recommender system comes to deal with new products or the products have not been evaluated by consumers. This paper addresses this problem based on a comparison of product specifications, experiments were conducted in the recommendation domain of digital cameras.

引用

页数：8

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