607 citations · 2.2k across the 78 of their papers we have counts for
17 papers · 1 filter
Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach
Hyungsul Kim, Ahmed El-Kishky, Xiang Ren +1
We present ProxiModel, a novel event mining framework for extracting high-quality structured event knowledge from large, redundant, and noisy news data sources. The proposed model…
Relation Learning on Social Networks with Multi-Modal Graph Edge Variational Autoencoders
Carl Yang, Jieyu Zhang, Haonan Wang +5
While node semantics have been extensively explored in social networks, little research attention has been paid to profile edge semantics, i.e., social relations. Ideal edge semant…
Spherical Text Embedding
Yu Meng, Jiaxin Huang, Guangyuan Wang +4
Unsupervised text embedding has shown great power in a wide range of NLP tasks. While text embeddings are typically learned in the Euclidean space, directional similarity is often…
Unsupervised Attributed Multiplex Network Embedding
Chanyoung Park, Donghyun Kim, Jiawei Han +1
Nodes in a multiplex network are connected by multiple types of relations. However, most existing network embedding methods assume that only a single type of relation exists betwee…
HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories
Yu Zhang, Frank F. Xu, Sha Li +4
GitHub has become an important platform for code sharing and scientific exchange. With the massive number of repositories available, there is a pressing need for topic-based search…
FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams
Wanzheng Zhu, Hongyu Gong, Jiaming Shen +4
Set expansion aims to expand a small set of seed entities into a complete set of relevant entities. Most existing approaches assume the input seed set is unambiguous and completely…
CubeNet: Multi-Facet Hierarchical Heterogeneous Network Construction, Analysis, and Mining
Carl Yang, Dai Teng, Siyang Liu +8
Due to the ever-increasing size of data, construction, analysis and mining of universal massive networks are becoming forbidden and meaningless. In this work, we outline a novel fr…
Neural Embedding Propagation on Heterogeneous Networks
Carl Yang, Jieyu Zhang, Jiawei Han
Classification is one of the most important problems in machine learning. To address label scarcity, semi-supervised learning (SSL) has been intensively studied over the past two d…
Query-Specific Knowledge Summarization with Entity Evolutionary Networks
Carl Yang, Lingrui Gan, Zongyi Wang +3
Given a query, unlike traditional IR that finds relevant documents or entities, in this work, we focus on retrieving both entities and their connections for insightful knowledge su…
Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity
Yu Shi, Jiaming Shen, Yuchen Li +7
Text-rich heterogeneous information networks (text-rich HINs) are ubiquitous in real-world applications. Hypernymy, also known as is-a relation or subclass-of relation, lays in the…
CrossWeigh: Training Named Entity Tagger from Imperfect Annotations
Zihan Wang, Jingbo Shang, Liyuan Liu +3
Everyone makes mistakes. So do human annotators when curating labels for named entity recognition (NER). Such label mistakes might hurt model training and interfere model compariso…
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…
Raw-to-End Name Entity Recognition in Social Media
Liyuan Liu, Zihan Wang, Jingbo Shang +5
Taking word sequences as the input, typical named entity recognition (NER) models neglect errors from pre-processing (e.g., tokenization). However, these errors can influence the m…
Facet-Aware Evaluation for Extractive Summarization
Yuning Mao, Liyuan Liu, Qi Zhu +2
Commonly adopted metrics for extractive summarization focus on lexical overlap at the token level. In this paper, we present a facet-aware evaluation setup for better assessment of…
Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings
Ahmed El-Kishky, Frank Xu, Aston Zhang +1
Traditionally, many text-mining tasks treat individual word-tokens as the finest meaningful semantic granularity. However, in many languages and specialized corpora, words are comp…
Discriminative Topic Mining via Category-Name Guided Text Embedding
Yu Meng, Jiaxin Huang, Guangyuan Wang +4
Mining a set of meaningful and distinctive topics automatically from massive text corpora has broad applications. Existing topic models, however, typically work in a purely unsuper…
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu, Haoming Jiang, Pengcheng He +4
The learning rate warmup heuristic achieves remarkable success in stabilizing training, accelerating convergence and improving generalization for adaptive stochastic optimization a…