activity
20162021
most citedSnippext: Semi-supervised Opinion Mining with Augmented Data

54 citations · 56 across the 5 of their papers we have counts for

collaborators

10 papers

cs.DB2021

TCUDB: Accelerating Database with Tensor Processors

Yu-Ching Hu, Yuliang Li, Hung-Wei Tseng

The emergence of novel hardware accelerators has powered the tremendous growth of machine learning in recent years. These accelerators deliver incomparable performance gains in pro…

cs.CL2020

Deep or Simple Models for Semantic Tagging? It Depends on your Data [Experiments]

Jinfeng Li, Yuliang Li, Xiaolan Wang +1

Semantic tagging, which has extensive applications in text mining, predicts whether a given piece of text conveys the meaning of a given semantic tag. The problem of semantic taggi…

cs.CL20201 cited

Enhancing Review Comprehension with Domain-Specific Commonsense

Aaron Traylor, Chen Chen, Behzad Golshan +6

Review comprehension has played an increasingly important role in improving the quality of online services and products and commonsense knowledge can further enhance review compreh…

cs.DB2020

Deep Entity Matching with Pre-Trained Language Models

Yuliang Li, Jinfeng Li, Yoshihiko Suhara +2

We present Ditto, a novel entity matching system based on pre-trained Transformer-based language models. We fine-tune and cast EM as a sequence-pair classification problem to lever…

cs.CL202054 cited

Snippext: Semi-supervised Opinion Mining with Augmented Data

Zhengjie Miao, Yuliang Li, Xiaolan Wang +1

Online services are interested in solutions to opinion mining, which is the problem of extracting aspects, opinions, and sentiments from text. One method to mine opinions is to lev…

cs.HC2020

Teddy: A System for Interactive Review Analysis

Xiong Zhang, Jonathan Engel, Sara Evensen +3

Reviews are integral to e-commerce services and products. They contain a wealth of information about the opinions and experiences of users, which can help better understand consume…