H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 34 Citations 4,711 118 World Ranking 6392 National Ranking 614

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Sujian Li spends much of his time researching Artificial intelligence, Natural language processing, Automatic summarization, Artificial neural network and Parsing. His study focuses on the intersection of Artificial intelligence and fields such as Machine learning with connections in the field of Perspective. The various areas that Sujian Li examines in his Natural language processing study include Context and Reading.

His work on Multi-document summarization as part of his general Automatic summarization study is frequently connected to Semantic HTML, thereby bridging the divide between different branches of science. His work carried out in the field of Artificial neural network brings together such families of science as Annotation and Convolutional neural network. The concepts of his Parsing study are interwoven with issues in Dependency, Discourse connectives and Multi-task learning.

His most cited work include:

  • Interactive attention networks for aspect-level sentiment classification (259 citations)
  • Ranking with recursive neural networks and its application to multi-document summarization (156 citations)
  • A Dependency-Based Neural Network for Relation Classification (125 citations)

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

Sujian Li mainly investigates Artificial intelligence, Natural language processing, Automatic summarization, Information retrieval and Sentence. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning. His studies in Natural language processing integrate themes in fields like Machine reading, Comprehension and Context.

The Automatic summarization study combines topics in areas such as Ranking and Benchmark. His study looks at the intersection of Information retrieval and topics like Data mining with Information extraction. His Sentence research includes themes of Representation and Support vector machine.

He most often published in these fields:

  • Artificial intelligence (75.30%)
  • Natural language processing (60.84%)
  • Automatic summarization (28.92%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (75.30%)
  • Natural language processing (60.84%)
  • Automatic summarization (28.92%)

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

The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Automatic summarization, Question answering and Sentence. His Artificial intelligence research incorporates elements of Machine reading and Comprehension. His Natural language processing research is multidisciplinary, relying on both Deep learning and Discourse analysis.

His Deep learning research incorporates themes from Artificial neural network and Convolutional neural network. His research investigates the connection with Automatic summarization and areas like WordNet which intersect with concerns in Semantic relevance and Sentence ranking. His Sentence study combines topics from a wide range of disciplines, such as Paragraph, Boosting, Learnability and Reinforcement learning.

Between 2017 and 2021, his most popular works were:

  • Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization (118 citations)
  • Do NLP Models Know Numbers? Probing Numeracy in Embeddings (68 citations)
  • Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading Comprehension (61 citations)

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

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Sujian Li mostly deals with Artificial intelligence, Natural language processing, Comprehension, Machine reading and Word. Sujian Li focuses mostly in the field of Artificial intelligence, narrowing it down to topics relating to Machine learning and, in certain cases, Joint. His work on Question answering, BLEU and Automatic summarization as part of general Natural language processing study is frequently linked to Mechanism and Order, therefore connecting diverse disciplines of science.

His Automatic summarization study integrates concerns from other disciplines, such as Stability, Readability, Template based, Text simplification and Source text. His Comprehension research is multidisciplinary, incorporating elements of Margin, Search engine and Language model. The study incorporates disciplines such as Relationship extraction, Speech recognition, Artificial neural network and Meaning in addition to Word.

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.

Best Publications

Interactive attention networks for aspect-level sentiment classification

Dehong Ma;Sujian Li;Xiaodong Zhang;Houfeng Wang.
international joint conference on artificial intelligence (2017)

426 Citations

Ranking with recursive neural networks and its application to multi-document summarization

Ziqiang Cao;Furu Wei;Li Dong;Sujian Li.
national conference on artificial intelligence (2015)

228 Citations

Applying regression models to query-focused multi-document summarization

You Ouyang;Wenjie Li;Sujian Li;Qin Lu.
Information Processing and Management (2011)

183 Citations

A Dependency-Based Neural Network for Relation Classification

Yang Liu;Furu Wei;Sujian Li;Heng Ji.
international joint conference on natural language processing (2015)

164 Citations

Entity-centric topic-oriented opinion summarization in twitter

Xinfan Meng;Furu Wei;Xiaohua Liu;Ming Zhou.
knowledge discovery and data mining (2012)

157 Citations

Semantic computation in a Chinese question-answering system

Sujian Li;Jian Zhang;Xiong Huang;Shuo Bai.
Journal of Computer Science and Technology (2002)

130 Citations

A novel neural topic model and its supervised extension

Ziqiang Cao;Sujian Li;Yang Liu;Wenjie Li.
national conference on artificial intelligence (2015)

129 Citations

Do NLP Models Know Numbers? Probing Numeracy in Embeddings

Eric Wallace;Yizhong Wang;Sujian Li;Sameer Singh.
empirical methods in natural language processing (2019)

119 Citations

Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization

Ziqiang Cao;Wenjie Li;Sujian Li;Furu Wei.
meeting of the association for computational linguistics (2018)

118 Citations

Learning Summary Prior Representation for Extractive Summarization

Ziqiang Cao;Furu Wei;Sujian Li;Wenjie Li.
international joint conference on natural language processing (2015)

111 Citations

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Best Scientists Citing Sujian Li

Heng Ji

Heng Ji

University of Illinois at Urbana-Champaign

Publications: 41

Guodong Zhou

Guodong Zhou

Soochow University

Publications: 27

Xiaojun Wan

Xiaojun Wan

Peking University

Publications: 24

Giuseppe Carenini

Giuseppe Carenini

University of British Columbia

Publications: 24

Hai Zhao

Hai Zhao

Shanghai Jiao Tong University

Publications: 24

Min Zhang

Min Zhang

Tsinghua University

Publications: 23

Xuanjing Huang

Xuanjing Huang

Fudan University

Publications: 23

Xipeng Qiu

Xipeng Qiu

Fudan University

Publications: 22

Furu Wei

Furu Wei

Microsoft (United States)

Publications: 19

Wenjie Li

Wenjie Li

Hong Kong Polytechnic University

Publications: 19

Mirella Lapata

Mirella Lapata

University of Edinburgh

Publications: 17

Jie Zhou

Jie Zhou

Tsinghua University

Publications: 17

Ting Liu

Ting Liu

Harbin Institute of Technology

Publications: 16

Maosong Sun

Maosong Sun

Tsinghua University

Publications: 15

Dongyan Zhao

Dongyan Zhao

Peking University

Publications: 15

Jun Zhao

Jun Zhao

Chinese Academy of Sciences

Publications: 15

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