Using semantic web to reduce the cold-start problems in recommendation systems

被引：2

作者：

Nouali, Omar ^{[1
]}

Belloui, Amokrane ^{[1
]}

机构：

[1] INI, CERIST, Algiers, Algeria

来源：

2009 SECOND INTERNATIONAL CONFERENCE ON THE APPLICATIONS OF DIGITAL INFORMATION AND WEB TECHNOLOGIES (ICADIWT 2009) | 2009年

关键词：

D O I：

10.1109/ICADIWT.2009.5273972

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Collaborative filtering systems suffer from the cold-start problems (evaluation matrix, new user/new resource problem...). In this paper, we show that using semantic information describing users and resources can reduce the problems and lead to a better precision, coverage and quality for the recommendation engine. Semantic web is the infrastructure used for managing such semantic descriptions. We also present here the results of a set of evaluation experiments.

引用

页码：525 / 530

页数：6

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