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 32 Citations 5,027 223 World Ranking 7550 National Ranking 218

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • The Internet

Yuefeng Li mostly deals with Information retrieval, Data mining, Ontology, Text mining and Ontology. Yuefeng Li interconnects World Wide Web and Personalization in the investigation of issues within Information retrieval. His Data mining study integrates concerns from other disciplines, such as Information filtering system and Web mining.

His Ontology research incorporates elements of Domain, Fuzzy set, Fuzzy logic and Search engine. His Text mining study combines topics in areas such as The Internet, Polysemy, Artificial intelligence, Machine learning and Concept mining. His studies deal with areas such as Web standards, Web design, Web mapping and Web modeling as well as Social Semantic Web.

His most cited work include:

  • Effective Pattern Discovery for Text Mining (246 citations)
  • Mining ontology for automatically acquiring Web user information needs (168 citations)
  • The state-of-the-art in personalized recommender systems for social networking (138 citations)

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

Yuefeng Li focuses on Information retrieval, Data mining, Artificial intelligence, Ontology and Association rule learning. Information retrieval is often connected to World Wide Web in his work. The concepts of his Data mining study are interwoven with issues in Information filtering system, Set, Cluster analysis and Decision rule.

His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning, Pattern recognition and Natural language processing. His research in the fields of Upper ontology, Ontology-based data integration and Process ontology overlaps with other disciplines such as Ontology. He has included themes like Quality and Association in his Association rule learning study.

He most often published in these fields:

  • Information retrieval (46.91%)
  • Data mining (29.64%)
  • Artificial intelligence (22.15%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (22.15%)
  • Topic model (11.40%)
  • Information retrieval (46.91%)

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

His primary scientific interests are in Artificial intelligence, Topic model, Information retrieval, Feature selection and Ontology. His research integrates issues of Machine learning and Natural language processing in his study of Artificial intelligence. His Topic model study combines topics in areas such as Baseline, Set, Relevance, Text mining and Discriminative model.

His biological study spans a wide range of topics, including Semantic similarity and Sensor fusion. His Information retrieval study combines topics from a wide range of disciplines, such as Quality, Context, Representation, Selection and Microblogging. His work on Ontology learning is typically connected to Ontology and Matching as part of general Ontology study, connecting several disciplines of science.

Between 2015 and 2021, his most popular works were:

  • Enhancing Binary Classification by Modeling Uncertain Boundary in Three-Way Decisions (29 citations)
  • Effective pseudo-relevance for Microblog retrieval (12 citations)
  • Dual pattern-enhanced representations model for query-focused multi-document summarisation (8 citations)

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

  • Artificial intelligence
  • Machine learning
  • The Internet

The scientist’s investigation covers issues in Information retrieval, Topic model, Discriminative model, Relevance and Context. His Information retrieval research is mostly focused on the topic Ontology. While the research belongs to areas of Topic model, Yuefeng Li spends his time largely on the problem of Information needs, intersecting his research to questions surrounding DUAL, Sentence, Data modeling, Personalization and Ontology learning.

His Relevance research is multidisciplinary, incorporating perspectives in Polysemy, Data mining and Feature selection. The Data mining study combines topics in areas such as Cluster analysis and Dynamic topic model. His Context research includes themes of Word embedding, Artificial intelligence and Natural language processing.

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

Effective Pattern Discovery for Text Mining

Ning Zhong;Yuefeng Li;Sheng-Tang Wu.
IEEE Transactions on Knowledge and Data Engineering (2012)

429 Citations

Mining ontology for automatically acquiring Web user information needs

Yuefeng Li;Ning Zhong.
IEEE Transactions on Knowledge and Data Engineering (2006)

257 Citations

The state-of-the-art in personalized recommender systems for social networking

Xujuan Zhou;Yue Xu;Yuefeng Li;Audun Josang.
Artificial Intelligence Review (2012)

236 Citations

Text mining and probabilistic language modeling for online review spam detection

Raymond Y. K. Lau;S. Y. Liao;Ron Chi-Wai Kwok;Kaiquan Xu.
acm transactions on management information systems (2012)

218 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

Deploying Approaches for Pattern Refinement in Text Mining

Sheng-tang Wu;Yuefeng Li;Yue Xu.
international conference on data mining (2006)

171 Citations

A Personalized Ontology Model for Web Information Gathering

Xiaohui Tao;Yuefeng Li;Ning Zhong.
IEEE Transactions on Knowledge and Data Engineering (2011)

166 Citations

Granule Based Intertransaction Association Rule Mining

Wanzhong Yang;Yuefeng Li;Yue Xu.
international conference on tools with artificial intelligence (2007)

166 Citations

Automatic Pattern-Taxonomy Extraction for Web Mining

Sheng-Tang Wu;Yuefeng Li;Yue Xu;Binh Pham.
web intelligence (2004)

161 Citations

An information filtering model on the Web and its application in JobAgent

Y. Li;C. Zhang;J. R. Swan.
Knowledge Based Systems (2000)

149 Citations

Editorial Boards

Best Scientists Citing Yuefeng Li

Raymond Y. K. Lau

Raymond Y. K. Lau

City University of Hong Kong

Publications: 33

Dun Liu

Dun Liu

Southwest Jiaotong University

Publications: 19

Yiyu Yao

Yiyu Yao

University of Regina

Publications: 15

Ning Zhong

Ning Zhong

Maebashi Institute of Technology

Publications: 10

Gabriella Pasi

Gabriella Pasi

University of Milano-Bicocca

Publications: 8

Thomas Stützle

Thomas Stützle

Université Libre de Bruxelles

Publications: 8

Tianrui Li

Tianrui Li

Southwest Jiaotong University

Publications: 8

Antonio Hernando

Antonio Hernando

Spanish National Research Council

Publications: 6

Peter Bruza

Peter Bruza

Queensland University of Technology

Publications: 5

Longbing Cao

Longbing Cao

University of Technology Sydney

Publications: 5

Jie Zhang

Jie Zhang

Nanyang Technological University

Publications: 5

Witold Pedrycz

Witold Pedrycz

University of Alberta

Publications: 5

Jian Ma

Jian Ma

Southwest Jiaotong University

Publications: 5

Xindong Wu

Xindong Wu

Hefei University of Technology

Publications: 5

Lei Zhang

Lei Zhang

International Digital Economy Academy

Publications: 5

Wei-Ying Ma

Wei-Ying Ma

Tsinghua University

Publications: 5

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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