462 citations · 1.5k across the 58 of their papers we have counts for
6 papers · 2 filters
Weakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning
Meng Qu, Xiang Ren, Yu Zhang +1
Extracting relations from text corpora is an important task in text mining. It becomes particularly challenging when focusing on weakly-supervised relation extraction, that is, uti…
Indirect Supervision for Relation Extraction using Question-Answer Pairs
Zeqiu Wu, Xiang Ren, Frank F. Xu +2
Automatic relation extraction (RE) for types of interest is of great importance for interpreting massive text corpora in an efficient manner. Traditional RE models have heavily rel…
Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach
Liyuan Liu, Xiang Ren, Qi Zhu +4
Relation extraction is a fundamental task in information extraction. Most existing methods have heavy reliance on annotations labeled by human experts, which are costly and time-co…
Automatic Synonym Discovery with Knowledge Bases
Meng Qu, Xiang Ren, Jiawei Han
Recognizing entity synonyms from text has become a crucial task in many entity-leveraging applications. However, discovering entity synonyms from domain-specific text corpora (e.g.…
MetaPAD: Meta Pattern Discovery from Massive Text Corpora
Meng Jiang, Jingbo Shang, Taylor Cassidy +4
Mining textual patterns in news, tweets, papers, and many other kinds of text corpora has been an active theme in text mining and NLP research. Previous studies adopt a dependency…
Automated Phrase Mining from Massive Text Corpora
Jingbo Shang, Jialu Liu, Meng Jiang +3
As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus. Phrase mining is important in various tasks such as informati…