Reasoning is a fundamental capability for distilling valuable information from knowledge graphs. Existing work has primarily been focusing on point-wise reasoning, including search, link predication, entity prediction, subgraph matching and so on. We introduce comparative reasoning over knowledge graphs, which aims to infer the commonality and inconsistency with respect to multiple pieces of clues.
We develop a large-scale prototype system that integrates various point-wise reasoning functions as well as the newly proposed comparative reasoning capability over knowledge graphs. We present both the system architecture and its key functions.
Lihui Liu (University of Illinois at Urbana Champaign)
Boxin Du (University of Illinois at Urbana-Champaign)
Heng Ji (University of Illinois)
Hanghang Tong (University of Illinois at Urbana-Champaign)
More from the Same Authors
2020 Poster: Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering »
Long Chen · Yuan Yao · Feng Xu · Miao Xu · Hanghang Tong