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近年来，多跳知识库问答（Knowledge Base Question Answering, KBQA）获得了广泛的关注。 由于标注整个多跳推理过程代价较高，通常只能获得弱监督信号（问题答案对）训练模型，而中间推理过程的标注缺失。 受此影响，模型常通过歧义推理得到正确答案，训练数据无法得到有效利用。为解决此挑战，本文提出基于双向推理自动为多跳知识库问答任务学习中间监督信号。 zhihu
近年来，知识图谱（KB）被广泛应用于推荐系统（RS），但公开将推荐系统物品链接到知识图谱实体的数据集还较少。本文结合SIGIR2018论文《Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks》所用数据集，公布了相关链接数据集，希望能对大家有所帮助。zhihu
Picture at Museo Nazionale del Cinema in Turing, Italy
Picture taken at Marina Bay, Singapore
Published in WSDM, 2019
In this paper, we have proposed a novel Taxonomy-aware Multi-hop Reasoning Network (TMRN) for better understandin2g-haonpd modeling user preference for sequential recommendation. We have associated the learning of user preferences with the category hierarchy. For more details, please click the title.
Recommended citation: Huang, J., Ren, Z., Zhao, W. X., He, G., Wen, J. R., & Dong, D. (2019, January). Taxonomy-aware multi-hop reasoning networks for sequential recommendation. In Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining (pp. 573-581). https://dl.acm.org/doi/abs/10.1145/3289600.3290972
Published in Data Intelligence Journal, 2019
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. For more details, please click the title.
Recommended citation: Wayne Xin Zhao, Gaole He, Kunlin Yang, Hong-Jian Dou, Jin Huang,Siqi Ouyang and Ji-Rong Wen. KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems. Data Intelligence 2019. http://RichardHGL.github.io/files/KB4Rec.pdf
Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning
Published in WWW, 2020
In this paper, we take a new perspective that aims to leverage rich user-item interaction data (user interaction data for short) for improving the KGC task. For more details, please click the title.
Recommended citation: Gaole He, Junyi Li, Wayne Xin Zhao, Peiju Liu and Ji-Rong Wen (2020). Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning. In WWW 2020, Taipei, Taiwan, China, April 20–24, 2020. http://RichardHGL.github.io/files/www2020.pdf
Published in CIKM, 2020
Personalized review generation (PRG) aims to automatically produce personalized review text, which is a challenging natural language generation task. In this paper, we propose a novel knowledge-enhanced PRG model based on capsule graph neural network (Caps-GNN).. For more details, please click the title.
Recommended citation: Junyi Li, Siqing Li, Wayne Xin Zhao*, Gaole He, Zhicheng Wei, Nicholas Jing Yuan, Ji-Rong Wen. Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network. In CIKM 2020. http://RichardHGL.github.io/publication/2020-10-19-paper-cikm
Published in WSDM, 2021
To address weak supervision challenge, we propose a novel teacher-student approach for the multi-hop KBQA task. For more details, please click the title.
Recommended citation: Gaole He, Yunshi Lan, Jing Jiang, Wayne Xin Zhao and Ji-Rong Wen (2021). Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals. paper, slides, poster, video. In WSDM 2021. Online, March 8–12, 2021. http://RichardHGL.github.io/files/wsdm2021.pdf
This is my first paper accepted as the first author, I give a short talk on our work. The video can be found at here.
This is a paper talk about our paper accepted by WWW 2020, at EARS workshop of SIGIR 2020.
This work was done when I visited Singpore Management University. I give a oral talk on our work. The video can be found at here.
Freshman Guide, Renmin University of China, Turning class, 2018
The main duty is to help freshman get familiar with life and lessons about university. As I graduated from the school of information, I’m familiar with both life and lessons here.