83 citations · 292 across the 25 of their papers we have counts for
6 papers · 1 filter
Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations
Qingkai Zeng, Jinfeng Lin, Wenhao Yu +2
Automatic construction of a taxonomy supports many applications in e-commerce, web search, and question answering. Existing taxonomy expansion or completion methods assume that new…
Cross-Network Learning with Partially Aligned Graph Convolutional Networks
Meng Jiang
Graph neural networks have been widely used for learning representations of nodes for many downstream tasks on graph data. Existing models were designed for the nodes on a single g…
Learning from Counterfactual Links for Link Prediction
Tong Zhao, Gang Liu, Daheng Wang +2
Learning to predict missing links is important for many graph-based applications. Existing methods were designed to learn the association between observed graph structure and exist…
Modeling multi-scale data via a network of networks
Shawn Gu, Meng Jiang, Pietro Hiram Guzzi +1
Prediction of node and graph labels are prominent network science tasks. Data analyzed in these tasks are sometimes related: entities represented by nodes in a higher-level (higher…
Sentence-Permuted Paragraph Generation
Wenhao Yu, Chenguang Zhu, Tong Zhao +2
Generating paragraphs of diverse contents is important in many applications. Existing generation models produce similar contents from homogenized contexts due to the fixed left-to-…
TCN: Table Convolutional Network for Web Table Interpretation
Daheng Wang, Prashant Shiralkar, Colin Lockard +3
Information extraction from semi-structured webpages provides valuable long-tailed facts for augmenting knowledge graph. Relational Web tables are a critical component containing a…