Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2014)

被引：3

作者：

Bogers, Toine ^{[1
]}

Koolen, Marijn ^{[2
]}

Cantador, Ivan ^{[3
]}

机构：

[1] Aalborg Univ, Dept Commun & Psychol, DK-2450 Copenhagen, Denmark

[2] Univ Amsterdam, Inst Log Language & Computat, Amsterdam, Netherlands

[3] Univ Autonoma Madrid, Escuela Politecn Super, Madrid 28049, Spain

来源：

PROCEEDINGS OF THE 8TH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS'14) | 2014年

关键词：

recommender systems; content-based recommendation; text reviews; user-generated content; implicit feedback; semantics; context;

D O I：

10.1145/2645710.2645784

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2014 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.

引用

页码：379 / 380

页数：2