14 citations · 29 across the 8 of their papers we have counts for
7 papers
Complex Evolutional Pattern Learning for Temporal Knowledge Graph Reasoning
Zixuan Li, Saiping Guan, Xiaolong Jin +7
A Temporal Knowledge Graph (TKG) is a sequence of KGs corresponding to different timestamps. TKG reasoning aims to predict potential facts in the future given the historical KG seq…
Integrating Deep Event-Level and Script-Level Information for Script Event Prediction
Long Bai, Saiping Guan, Jiafeng Guo +3
Scripts are structured sequences of events together with the participants, which are extracted from the texts.Script event prediction aims to predict the subsequent event given the…
Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs
Zixuan Li, Xiaolong Jin, Saiping Guan +4
Temporal Knowledge Graphs (TKGs) have been developed and used in many different areas. Reasoning on TKGs that predicts potential facts (events) in the future brings great challenge…
Link Prediction on N-ary Relational Data Based on Relatedness Evaluation
Saiping Guan, Xiaolong Jin, Jiafeng Guo +2
With the overwhelming popularity of Knowledge Graphs (KGs), researchers have poured attention to link prediction to fill in missing facts for a long time. However, they mainly focu…
Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning
Zixuan Li, Xiaolong Jin, Wei Li +5
Knowledge Graph (KG) reasoning that predicts missing facts for incomplete KGs has been widely explored. However, reasoning over Temporal KG (TKG) that predicts facts in the future…
Modeling and Predicting Popularity Dynamics of Microblogs using Self-Excited Hawkes Processes
Peng Bao, Hua-Wei Shen, Xiaolong Jin +1
The ability to model and predict the popularity dynamics of individual user generated items on online media has important implications in a wide range of areas. In this paper, we p…