KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems

被引：129

作者：

Zhao, Wayne Xin ^{[1
]}

He, Gaole ^{[1
]}

Yang, Kunlin ^{[1
]}

Dou, Hongjian ^{[1
]}

Huang, Jin ^{[1
]}

Ouyang, Siqi ^{[2
]}

Wen, Ji-Rong ^{[1
]}

机构：

[1] Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China

[2] Cornell Tech, Jacobs Technion Cornell Inst, New York, NY 10044 USA

来源：

DATA INTELLIGENCE | 2019年 / 1卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Knowledge-aware recommendation; Recommender system; Knowledge base;

D O I：

10.1162/dint_a_00008

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

080201 [机械制造及其自动化];

摘要：

To develop a knowledge-aware recommender system, a key issue is how to obtain rich and structured knowledge base (KB) information for recommender system (RS) items. Existing data sets or methods either use side information from original RSs (containing very few kinds of useful information) or utilize a private KB. In this paper, we present KB4Rec v1.0, a data set linking KB information for RSs. It has linked three widely used RS data sets with two popular KBs, namely Freebase and YAGO. Based on our linked data set, we first preform qualitative analysis experiments, and then we discuss the effect of two important factors (i.e., popularity and recency) on whether a RS item can be linked to a KB entity. Finally, we compare several knowledge-aware recommendation algorithms on our linked data set.

引用

页码：121 / 136

页数：16

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