H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 42 Citations 8,494 174 World Ranking 4139 National Ranking 383

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Minlie Huang mostly deals with Artificial intelligence, Natural language processing, Machine learning, Information retrieval and Conversation. In his research, Minlie Huang performs multidisciplinary study on Artificial intelligence and Protein–protein interaction. His study in Natural language processing is interdisciplinary in nature, drawing from both Annotation and Conjunction.

His work deals with themes such as Information extraction and Forum spam, Spambot, which intersect with Machine learning. Minlie Huang combines subjects such as Ranking, Context, World Wide Web and Biological database with his study of Information retrieval. His Conversation research includes themes of Commonsense knowledge and Vocabulary.

His most cited work include:

  • Attention-based LSTM for Aspect-level Sentiment Classification (696 citations)
  • Learning to identify review spam (253 citations)
  • Structure-Aware Review Mining and Summarization (234 citations)

What are the main themes of his work throughout his whole career to date?

Minlie Huang mainly focuses on Artificial intelligence, Natural language processing, Machine learning, Human–computer interaction and Dialog box. Artificial intelligence is closely attributed to Context in his research. His Natural language processing research incorporates themes from Commonsense knowledge and Comprehension.

His work carried out in the field of Machine learning brings together such families of science as Text mining, Generative model and Robustness. The Human–computer interaction study combines topics in areas such as Semantics, Conversation, State and Reinforcement learning. His Dialog box research is multidisciplinary, relying on both Task oriented and Component.

He most often published in these fields:

  • Artificial intelligence (54.17%)
  • Natural language processing (32.87%)
  • Machine learning (17.59%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (54.17%)
  • Dialog box (16.67%)
  • Human–computer interaction (17.13%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Dialog box, Human–computer interaction, Natural language processing and Conversation. Artificial intelligence and Machine learning are frequently intertwined in his study. His work in the fields of Leverage overlaps with other areas such as Beam search.

His Dialog system study in the realm of Dialog box connects with subjects such as Multi domain. His studies deal with areas such as Variety, Component and Reinforcement learning as well as Human–computer interaction. His work deals with themes such as Context, Self training and Knowledge graph, which intersect with Natural language processing.

Between 2019 and 2021, his most popular works were:

  • Challenges in Building Intelligent Open-domain Dialog Systems (46 citations)
  • A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation (42 citations)
  • Robustness Verification for Transformers (17 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

The scientist’s investigation covers issues in Dialog box, Artificial intelligence, Natural language processing, Human–computer interaction and Dialog system. He has included themes like Domain, Semantics, Conversation and Component in his Dialog box study. His study in Repetition extends to Artificial intelligence with its themes.

His study in the field of Question answering also crosses realms of Base. His research in Human–computer interaction intersects with topics in Natural language, Decomposition, Domain knowledge and Reinforcement learning. The Dialog system study combines topics in areas such as Interpersonal communication and Task oriented.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Attention-based LSTM for Aspect-level Sentiment Classification

Yequan Wang;Minlie Huang;xiaoyan zhu;Li Zhao.
empirical methods in natural language processing (2016)

1118 Citations

Learning to identify review spam

Fangtao Li;Minlie Huang;Yi Yang;Xiaoyan Zhu.
international joint conference on artificial intelligence (2011)

422 Citations

Structure-Aware Review Mining and Summarization

Fangtao Li;Chao Han;Minlie Huang;Xiaoyan Zhu.
international conference on computational linguistics (2010)

354 Citations

Discovering patterns to extract protein--protein interactions from full texts

Minlie Huang;Xiaoyan Zhu;Yu Hao;Donald G. Payan.
Bioinformatics (2004)

315 Citations

Sentiment analysis with global topics and local dependency

Fangtao Li;Minlie Huang;Xiaoyan Zhu.
national conference on artificial intelligence (2010)

249 Citations

TransG : A Generative Model for Knowledge Graph Embedding

Han Xiao;Minlie Huang;Xiaoyan Zhu.
meeting of the association for computational linguistics (2016)

242 Citations

Commonsense Knowledge Aware Conversation Generation with Graph Attention

Hao Zhou;Tom Young;Minlie Huang;Haizhou Zhao.
international joint conference on artificial intelligence (2018)

202 Citations

Augmenting end-to-end dialogue systems with commonsense knowledge

Tom Young;Erik Cambria;Iti Chaturvedi;Hao Zhou.
national conference on artificial intelligence (2018)

195 Citations

The gene normalization task in BioCreative III

Zhiyong Lu;Hung-Yu Kao;Chih-Hsuan Wei;Minlie Huang.
BMC Bioinformatics (2011)

190 Citations

Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory.

Hao Zhou;Minlie Huang;Tianyang Zhang;Xiaoyan Zhu.
national conference on artificial intelligence (2017)

180 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Minlie Huang

Bing Liu

Bing Liu

Peking University

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Erik Cambria

Erik Cambria

Nanyang Technological University

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Zhiyong Lu

Zhiyong Lu

National Institutes of Health

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Maosong Sun

Maosong Sun

Tsinghua University

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Ting Liu

Ting Liu

Harbin Institute of Technology

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Soujanya Poria

Soujanya Poria

Singapore University of Technology and Design

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Jie Zhou

Jie Zhou

Tsinghua University

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Maarten de Rijke

Maarten de Rijke

University of Amsterdam

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Hua Wu

Hua Wu

Baidu (China)

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Rui Yan

Rui Yan

Renmin University of China

Publications: 25

Jun Zhao

Jun Zhao

Chinese Academy of Sciences

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Dongyan Zhao

Dongyan Zhao

Peking University

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Tat-Seng Chua

Tat-Seng Chua

National University of Singapore

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Bing Qin

Bing Qin

Harbin Institute of Technology

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Philip S. Yu

Philip S. Yu

University of Illinois at Chicago

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