D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 30 Citations 4,010 225 World Ranking 8795 National Ranking 833

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Dawei Song mainly focuses on Artificial intelligence, Information retrieval, Relevance, Language model and Natural language processing. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Quantum cognition and Pattern recognition. The Information retrieval study combines topics in areas such as Image, Data mining and Feature vector.

His studies in Relevance integrate themes in fields like Semantic computing, Context, Information needs and Semantic search. His study in the fields of Sentence under the domain of Natural language processing overlaps with other disciplines such as Information system, Track and Open university. His research in Sentence focuses on subjects like Set, which are connected to Query language and Query expansion.

His most cited work include:

  • Query expansion using term relationships in language models for information retrieval (167 citations)
  • Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning (137 citations)
  • Exploring EEG Features in Cross-Subject Emotion Recognition (84 citations)

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

Dawei Song mainly investigates Information retrieval, Artificial intelligence, Natural language processing, Relevance and Query expansion. His Information retrieval research is multidisciplinary, incorporating elements of Data mining and Personalization. His studies deal with areas such as Context, Machine learning and Pattern recognition as well as Artificial intelligence.

His Natural language processing study combines topics from a wide range of disciplines, such as Dependency and Inference. His Relevance research also works with subjects such as

  • Cognition that connect with fields like Quantum cognition,
  • Theoretical computer science and related Structure and Information needs. His study looks at the relationship between Query expansion and topics such as Query language, which overlap with Sargable and RDF query language.

He most often published in these fields:

  • Information retrieval (53.73%)
  • Artificial intelligence (46.27%)
  • Natural language processing (22.36%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (46.27%)
  • Natural language processing (22.36%)
  • Relevance (20.50%)

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

His primary areas of investigation include Artificial intelligence, Natural language processing, Relevance, Information retrieval and Sentiment analysis. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Machine learning. His Natural language processing study combines topics in areas such as Context, Convolution, Representation, Hilbert space and SemEval.

His research in Relevance intersects with topics in Learning to rank, Theoretical computer science, Cognition, Construct and Session. His Information retrieval study integrates concerns from other disciplines, such as Feature and Dimension. His Sentiment analysis study also includes

  • Conversation together with Interaction information,
  • Key which intersects with area such as Semantic gap.

Between 2016 and 2021, his most popular works were:

  • Exploring EEG Features in Cross-Subject Emotion Recognition (84 citations)
  • Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks. (61 citations)
  • A Tensorized Transformer for Language Modeling (42 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Sentiment analysis, Representation and Sentence. He conducts interdisciplinary study in the fields of Artificial intelligence and Quantum probability through his works. His study in Sentiment analysis is interdisciplinary in nature, drawing from both Range and Conversation.

His work carried out in the field of Representation brings together such families of science as Language model and Word. His Word study deals with Theoretical computer science intersecting with Information needs, Session search and Word embedding. Dawei Song has included themes like Artificial neural network and Quantum in his Sentence study.

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

Query expansion using term relationships in language models for information retrieval

Jing Bai;Dawei Song;Peter Bruza;Jian-Yun Nie.
conference on information and knowledge management (2005)

243 Citations

Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning

R.Y.K. Lau;Dawei Song;Yuefeng Li;T.C.H. Cheung.
IEEE Transactions on Knowledge and Data Engineering (2009)

208 Citations

Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks.

Chen Zhang;Qiuchi Li;Dawei Song.
empirical methods in natural language processing (2019)

173 Citations

Towards context sensitive information inference

D. Song;P. D. Bruza.
formal methods (2003)

126 Citations

Comparing dissimilarity measures for content-based image retrieval

Haiming Liu;Dawei Song;Stefan Rüger;Rui Hu.
asia information retrieval symposium (2008)

114 Citations

Exploring EEG Features in Cross-Subject Emotion Recognition

Xiang Li;Dawei Song;Peng Zhang;Yazhou Zhang.
Frontiers in Neuroscience (2018)

111 Citations

Advances in Information Retrieval Theory

Leif Azzopardi;Gabriella Kazai;Stephen Robertson;Stefan Rüger.
Lecture Notes in Computer Science (2009)

110 Citations

Emotion recognition from multi-channel EEG data through Convolutional Recurrent Neural Network

Xiang Li;Dawei Song;Peng Zhang;Guangliang Yu.
bioinformatics and biomedicine (2016)

106 Citations

Quantum-like non-separability of concept combinations, emergent associates and abduction

Peter D. Bruza;Kirsty Kitto;Brentyn J. Ramm;Laurianne Sitbon.
Logic Journal of The Igpl / Bulletin of The Igpl (2012)

77 Citations

Aboutness from a commonsense perspective

P. D. Bruza;D. W. Song;K. F. Wong.
Journal of the Association for Information Science and Technology (2000)

74 Citations

Best Scientists Citing Dawei Song

Raymond Y. K. Lau

Raymond Y. K. Lau

City University of Hong Kong

Publications: 37

Peter Bruza

Peter Bruza

Queensland University of Technology

Publications: 27

Yuefeng Li

Yuefeng Li

Queensland University of Technology

Publications: 23

Jian-Yun Nie

Jian-Yun Nie

University of Montreal

Publications: 22

Thomas Seidl

Thomas Seidl

Ludwig-Maximilians-Universität München

Publications: 14

Leif Azzopardi

Leif Azzopardi

University of Strathclyde

Publications: 13

Krisztian Balog

Krisztian Balog

University of Stavanger

Publications: 13

Qun Liu

Qun Liu

Huawei Technologies (China)

Publications: 10

Bin Hu

Bin Hu

Lanzhou University

Publications: 10

ChengXiang Zhai

ChengXiang Zhai

University of Illinois at Urbana-Champaign

Publications: 10

Allan Hanbury

Allan Hanbury

TU Wien

Publications: 10

Ji-Rong Wen

Ji-Rong Wen

Renmin University of China

Publications: 9

Maarten de Rijke

Maarten de Rijke

University of Amsterdam

Publications: 9

Dinh Phung

Dinh Phung

Monash University

Publications: 8

Mounia Lalmas

Mounia Lalmas

Spotify

Publications: 7

Liane Gabora

Liane Gabora

University of British Columbia

Publications: 7

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

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