b'Jingbo Shang'

Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks

Text categorization is an essential task in Web content analysis. Consid...
02/23/2021 ∙ by Xinyang Zhang, et al. ∙ 0 ∙ share

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Data Profiling for Adversarial Training: On the Ruin of Problematic Data

Multiple intriguing problems hover in adversarial training, including ro...
02/15/2021 ∙ by Chengyu Dong, et al. ∙ 0 ∙ share

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Sensei: Self-Supervised Sensor Name Segmentation

A sensor name, typically an alphanumeric string, encodes the key context...
01/01/2021 ∙ by Jiaman Wu, et al. ∙ 25 ∙ share

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X-Class: Text Classification with Extremely Weak Supervision

In this paper, we explore to conduct text classification with extremely ...
10/24/2020 ∙ by Zihan Wang, et al. ∙ 0 ∙ share

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Overfitting or Underfitting? Understand Robustness Drop in Adversarial Training

Our goal is to understand why the robustness drops after conducting adve...
10/15/2020 ∙ by Zichao Li, et al. ∙ 0 ∙ share

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User-Guided Aspect Classification for Domain-Specific Texts

Aspect classification, identifying aspects of text segments, facilitates...
04/30/2020 ∙ by Peiran Li, et al. ∙ 0 ∙ share

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SetExpan: Corpus-Based Set Expansion via Context Feature Selection and Rank Ensemble

Corpus-based set expansion (i.e., finding the "complete" set of entities...
10/17/2019 ∙ by Jiaming Shen, et al. ∙ 0 ∙ share

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FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams

Set expansion aims to expand a small set of seed entities into a complet...
10/10/2019 ∙ by Wanzheng Zhu, et al. ∙ 0 ∙ share

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CrossWeigh: Training Named Entity Tagger from Imperfect Annotations

Everyone makes mistakes. So do human annotators when curating labels for...
09/03/2019 ∙ by Zihan Wang, et al. ∙ 0 ∙ share

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Raw-to-End Name Entity Recognition in Social Media

Taking word sequences as the input, typical named entity recognition (NE...
08/14/2019 ∙ by Liyuan Liu, et al. ∙ 0 ∙ share

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Learning Named Entity Tagger using Domain-Specific Dictionary

Recent advances in deep neural models allow us to build reliable named e...
09/10/2018 ∙ by Jingbo Shang, et al. ∙ 0 ∙ share

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Entity Set Search of Scientific Literature: An Unsupervised Ranking Approach

Literature search is critical for any scientific research. Different fro...
04/29/2018 ∙ by Jiaming Shen, et al. ∙ 0 ∙ share

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Open Information Extraction with Global Structure Constraints

Extracting entities and their relations from text is an important task f...
04/26/2018 ∙ by Qi Zhu, et al. ∙ 0 ∙ share

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Integrating Local Context and Global Cohesiveness for Open Information Extraction

Extracting entities and their relations from text is an important task f...
04/26/2018 ∙ by Qi Zhu, et al. ∙ 0 ∙ share

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Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

Many efforts have been made to facilitate natural language processing ta...
04/20/2018 ∙ by Liyuan Liu, et al. ∙ 0 ∙ share

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Investigating Rumor News Using Agreement-Aware Search

In recent years, rumor news has been generated by humans as well as robo...
02/21/2018 ∙ by Jingbo Shang, et al. ∙ 0 ∙ share

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Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning

Motivation: Biomedical named entity recognition (BioNER) is the most fun...
01/30/2018 ∙ by Xuan Wang, et al. ∙ 0 ∙ share

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An Attention-based Collaboration Framework for Multi-View Network Representation Learning

Learning distributed node representations in networks has been attractin...
09/19/2017 ∙ by Meng Qu, et al. ∙ 0 ∙ share

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Empower Sequence Labeling with Task-Aware Neural Language Model

Linguistic sequence labeling is a general modeling approach that encompa...
09/13/2017 ∙ by Liyuan Liu, et al. ∙ 0 ∙ share

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MetaPAD: Meta Pattern Discovery from Massive Text Corpora

Mining textual patterns in news, tweets, papers, and many other kinds of...
03/13/2017 ∙ by Meng Jiang, et al. ∙ 0 ∙ share

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Automated Phrase Mining from Massive Text Corpora

As one of the fundamental tasks in text analysis, phrase mining aims at ...
02/15/2017 ∙ by Jingbo Shang, et al. ∙ 0 ∙ share

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DPPred: An Effective Prediction Framework with Concise Discriminative Patterns

In the literature, two series of models have been proposed to address pr...
10/31/2016 ∙ by Jingbo Shang, et al. ∙ 0 ∙ share

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A Parallel and Efficient Algorithm for Learning to Match

Many tasks in data mining and related fields can be formalized as matchi...
10/22/2014 ∙ by Jingbo Shang, et al. ∙ 0 ∙ share

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Jingbo Shang

Featured Co-authors

Yu Zhang

Chao Zhang

Jiawei Han

Jian Tang

Yong Yu

Xiang Ren

Hang Li

Jian Peng

Ming Zhang

Heng Ji

Qi Zhu

Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks

Data Profiling for Adversarial Training: On the Ruin of Problematic Data

Sensei: Self-Supervised Sensor Name Segmentation

X-Class: Text Classification with Extremely Weak Supervision

Overfitting or Underfitting? Understand Robustness Drop in Adversarial Training

User-Guided Aspect Classification for Domain-Specific Texts

SetExpan: Corpus-Based Set Expansion via Context Feature Selection and Rank Ensemble

FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams

CrossWeigh: Training Named Entity Tagger from Imperfect Annotations

Raw-to-End Name Entity Recognition in Social Media

Learning Named Entity Tagger using Domain-Specific Dictionary

Entity Set Search of Scientific Literature: An Unsupervised Ranking Approach

Open Information Extraction with Global Structure Constraints

Integrating Local Context and Global Cohesiveness for Open Information Extraction

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

Investigating Rumor News Using Agreement-Aware Search

Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning

An Attention-based Collaboration Framework for Multi-View Network Representation Learning

Empower Sequence Labeling with Task-Aware Neural Language Model

MetaPAD: Meta Pattern Discovery from Massive Text Corpora

Automated Phrase Mining from Massive Text Corpora

DPPred: An Effective Prediction Framework with Concise Discriminative Patterns

A Parallel and Efficient Algorithm for Learning to Match