Jointly Learning Explainable Rules for Recommendation with Knowledge Graph-Reference-Cited by-同舟云学术

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:The World Wide Web Conference on - WWW '19
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Author:

Ma Weizhi¹,Zhang Min¹,Cao Yue²,Jin Woojeong²,Wang Chenyang¹,Liu Yiqun¹,Ma Shaoping¹,Ren Xiang²

Affiliation:

1. Tsinghua University, China

2. University of Southern California, USA

Publisher

ACM Press

Reference49 articles.

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2. Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008. Freebase: a collaboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data. AcM, 1247-1250.

3. Rose Catherine and William Cohen. 2016. Personalized recommendations using knowledge graphs: A probabilistic logic programming approach. In Proceedings of the 10th ACM Conference on Recommender Systems. ACM, 325-332.

4. Rose Catherine, Kathryn Mazaitis, Maxine Eskenazi, and William Cohen. 2017. Explainable entity-based recommendations with knowledge graphs. arXiv preprint arXiv:1707.05254(2017).

5. Weiyu Cheng, Yanyan Shen, Yanmin Zhu, and Linpeng Huang. 2018. DELF: A Dual-Embedding based Deep Latent Factor Model for Recommendation.. In IJCAI. 3329-3335.

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