activity
20182020
most citedDistantly Supervised Named Entity Recognition using Positive-Unlabeled Learning

12 citations · 21 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CL2020

Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling

Yicheng Zou, Lujun Zhao, Yangyang Kang +7

In a customer service system, dialogue summarization can boost service efficiency by automatically creating summaries for long spoken dialogues in which customers and agents try to…

cs.LG2019

Weighed Domain-Invariant Representation Learning for Cross-domain Sentiment Analysis

Minlong Peng, Qi Zhang, Xuanjing Huang

Cross-domain sentiment analysis is currently a hot topic in the research and engineering areas. One of the most popular frameworks in this field is the domain-invariant representat…

cs.CL2019

Simplify the Usage of Lexicon in Chinese NER

Ruotian Ma, Minlong Peng, Qi Zhang +1

Recently, many works have tried to augment the performance of Chinese named entity recognition (NER) using word lexicons. As a representative, Lattice-LSTM (Zhang and Yang, 2018) h…

cs.CL201912 cited

Distantly Supervised Named Entity Recognition using Positive-Unlabeled Learning

Minlong Peng, Xiaoyu Xing, Qi Zhang +2

In this work, we explore the way to perform named entity recognition (NER) using only unlabeled data and named entity dictionaries. To this end, we formulate the task as a positive…

cs.CL20192 cited

Learning Task-specific Representation for Novel Words in Sequence Labeling

Minlong Peng, Qi Zhang, Xiaoyu Xing +3

Word representation is a key component in neural-network-based sequence labeling systems. However, representations of unseen or rare words trained on the end task are usually poor…

cs.LG20197 cited

Address Instance-level Label Prediction in Multiple Instance Learning

Minlong Peng, Qi Zhang

\textit{Multiple Instance Learning} (MIL) is concerned with learning from bags of instances, where only bag labels are given and instance labels are unknown. Existent approaches in…