19 citations · 57 across the 10 of their papers we have counts for
10 papers
Patton: Language Model Pretraining on Text-Rich Networks
Bowen Jin, Wentao Zhang, Yu Zhang +4
A real-world text corpus sometimes comprises not only text documents but also semantic links between them (e.g., academic papers in a bibliographic network are linked by citations…
The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study
Yu Zhang, Bowen Jin, Qi Zhu +2
Due to the exponential growth of scientific publications on the Web, there is a pressing need to tag each paper with fine-grained topics so that researchers can track their interes…
Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks
Bowen Jin, Yu Zhang, Qi Zhu +1
Representation learning on networks aims to derive a meaningful vector representation for each node, thereby facilitating downstream tasks such as link prediction, node classificat…
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…
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…
Task-Guided Pair Embedding in Heterogeneous Network
Chanyoung Park, Donghyun Kim, Qi Zhu +2
Many real-world tasks solved by heterogeneous network embedding methods can be cast as modeling the likelihood of pairwise relationship between two nodes. For example, the goal of…
Expert Finding in Heterogeneous Bibliographic Networks with Locally-trained Embeddings
Huan Gui, Qi Zhu, Liyuan Liu +2
Expert finding is an important task in both industry and academia. It is challenging to rank candidates with appropriate expertise for various queries. In addition, different types…
AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks
Yu Shi, Huan Gui, Qi Zhu +2
Heterogeneous information networks (HINs) are ubiquitous in real-world applications. Due to the heterogeneity in HINs, the typed edges may not fully align with each other. In order…
Wikidata Vandalism Detection - The Loganberry Vandalism Detector at WSDM Cup 2017
Qi Zhu, Hongwei Ng, Liyuan Liu +4
Wikidata is the new, large-scale knowledge base of the Wikimedia Foundation. As it can be edited by anyone, entries frequently get vandalized, leading to the possibility that it mi…
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…