no code implementations • 22 Nov 2021 • Jianhuan Zhuo, Qiannan Zhu, Yinliang Yue, Yuhong Zhao
The core objective of modelling recommender systems from implicit feedback is to maximize the positive sample score $s_p$ and minimize the negative sample score $s_n$, which can usually be summarized into two paradigms: the pointwise and the pairwise.
no code implementations • 2 Oct 2021 • Ren Li, Yanan Cao, Qiannan Zhu, Xiaoxue Li, Fang Fang
Modeling of relation pattern is the core focus of previous Knowledge Graph Embedding works, which represents how one entity is related to another semantically by some explicit relation.
1 code implementation • 24 Sep 2021 • Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li
However, most existing KGE works focus on the design of delicate triple modeling function, which mainly tells us how to measure the plausibility of observed triples, but offers limited explanation of why the methods can extrapolate to unseen data, and what are the important factors to help KGE extrapolate.
Ranked #9 on Link Prediction on FB15k-237
1 code implementation • 1 Jul 2020 • Yue Yuan, Xiaofei Zhou, Shirui Pan, Qiannan Zhu, Zeliang Song, Li Guo
Joint extraction of entities and relations is an important task in natural language processing (NLP), which aims to capture all relational triplets from plain texts.
Ranked #11 on Relation Extraction on WebNLG
1 code implementation • AAAI 2019 • Qiannan Zhu
With the rapid information explosion of news, making personalized news recommendation for users becomes an increasingly challenging problem.