most citedAutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

69 citations · 98 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL20206 cited

Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning

Yuning Mao, Yanru Qu, Yiqing Xie +2

While neural sequence learning methods have made significant progress in single-document summarization (SDS), they produce unsatisfactory results on multi-document summarization (M…

cs.AI202069 cited

AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

Xin Luna Dong, Xiang He, Andrey Kan +19

Can one build a knowledge graph (KG) for all products in the world? Knowledge graphs have firmly established themselves as valuable sources of information for search and question a…

cs.CL202018 cited

Octet: Online Catalog Taxonomy Enrichment with Self-Supervision

Yuning Mao, Tong Zhao, Andrey Kan +4

Taxonomies have found wide applications in various domains, especially online for item categorization, browsing, and search. Despite the prevalent use of online catalog taxonomies,…

cs.AI20205 cited

Learning Collaborative Agents with Rule Guidance for Knowledge Graph Reasoning

Deren Lei, Gangrong Jiang, Xiaotao Gu +3

Walk-based models have shown their advantages in knowledge graph (KG) reasoning by achieving decent performance while providing interpretable decisions. However, the sparse reward…

cs.CL2020

Generating Representative Headlines for News Stories

Xiaotao Gu, Yuning Mao, Jiawei Han +7

Millions of news articles are published online every day, which can be overwhelming for readers to follow. Grouping articles that are reporting the same event into news stories is…

cs.IR2019

Hierarchical Text Classification with Reinforced Label Assignment

Yuning Mao, Jingjing Tian, Jiawei Han +1

While existing hierarchical text classification (HTC) methods attempt to capture label hierarchies for model training, they either make local decisions regarding each label or comp…