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 47 Citations 7,965 238 World Ranking 3224 National Ranking 56

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Jie Zhang spends much of his time researching Computer security, Recommender system, Data mining, Robustness and Information retrieval. His work deals with themes such as Scalability, Buying agent, Multi-agent system, Vehicular ad hoc network and Computer network, which intersect with Computer security. His Recommender system study integrates concerns from other disciplines, such as Bayesian probability, Artificial intelligence and Competence.

His research in Data mining intersects with topics in Similarity, Server log and Web service. His research in Robustness tackles topics such as Intrusion detection system which are related to areas like Peer-to-peer and Correctness. His research investigates the link between Information retrieval and topics such as Order that cross with problems in Algorithm design, Advice and Preference.

His most cited work include:

  • Improved Light Harvesting and Improved Efficiency by Insertion of an Optical Spacer (ZnO) in Solution-Processed Small-Molecule Solar Cells (438 citations)
  • Efficient Solution‐Processed Small‐Molecule Solar Cells with Inverted Structure (427 citations)
  • Collaborative Security: A Survey and Taxonomy (333 citations)

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

Jie Zhang focuses on Artificial intelligence, Computer security, Machine learning, Recommender system and Robustness. His Artificial intelligence study typically links adjacent topics like Data mining. His study in Information retrieval extends to Data mining with its themes.

His work is connected to Collaborative filtering and Cold start, as a part of Recommender system. Robustness is closely attributed to Incentive in his work. Jie Zhang is interested in Social network, which is a field of World Wide Web.

He most often published in these fields:

  • Artificial intelligence (17.40%)
  • Computer security (10.90%)
  • Machine learning (10.67%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (17.40%)
  • Reinforcement learning (3.25%)
  • Theoretical computer science (3.71%)

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

Jie Zhang mainly focuses on Artificial intelligence, Reinforcement learning, Theoretical computer science, Recommender system and Machine learning. His Node research extends to Artificial intelligence, which is thematically connected. His Reinforcement learning study combines topics in areas such as Routing, Constraint, Heuristics, Scheme and Job shop scheduling.

His research on Recommender system also deals with topics like

  • Data science which is related to area like Empirical research,
  • World Wide Web most often made with reference to Baseline. His studies in Machine learning integrate themes in fields like Timeline and Focus. His work carried out in the field of Artificial neural network brings together such families of science as Computer security, Service provider, Bernoulli's principle and Genetic algorithm.

Between 2018 and 2021, his most popular works were:

  • Research commentary on recommendations with side information: A survey and research directions (29 citations)
  • Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach (17 citations)
  • Improving IoT Data Quality in Mobile Crowd Sensing: A Cross Validation Approach (17 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, Machine learning, Heuristics, Recommender system and Reinforcement learning. His biological study spans a wide range of topics, including Field and Random walk. The Machine learning study combines topics in areas such as Data stream, Layer and Accounting.

His work in Heuristics tackles topics such as Travelling salesman problem which are related to areas like Vehicle routing problem and Selection. His Recommender system study is concerned with the larger field of World Wide Web. His Reinforcement learning research incorporates elements of Scheme, Path, Graph and Inference.

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

Improved Light Harvesting and Improved Efficiency by Insertion of an Optical Spacer (ZnO) in Solution-Processed Small-Molecule Solar Cells

Aung Ko Ko Kyaw;Dong Hwan Wang;David Wynands;Jie Zhang.
Nano Letters (2013)

506 Citations

Efficient Solution‐Processed Small‐Molecule Solar Cells with Inverted Structure

Aung Ko Ko Kyaw;Dong Hwan Wang;Vinay Gupta;Vinay Gupta;Jie Zhang.
Advanced Materials (2013)

488 Citations

TrustSVD: collaborative filtering with both the explicit and implicit influence of user trust and of item ratings

Guibing Guo;Jie Zhang;Neil Yorke-Smith.
national conference on artificial intelligence (2015)

393 Citations

N-annulated perylene as an efficient electron donor for porphyrin-based dyes: enhanced light-harvesting ability and high-efficiency Co(II/III)-based dye-sensitized solar cells.

Jie Luo;Mingfei Xu;Renzhi Li;Kuo-Wei Huang.
Journal of the American Chemical Society (2014)

353 Citations

A Survey on Trust Management for VANETs

Jie Zhang.
advanced information networking and applications (2011)

282 Citations

Consistencies and contradictions of performance metrics in multiobjective optimization.

Siwei Jiang;Yew-Soon Ong;Jie Zhang;Liang Feng.
IEEE Transactions on Systems, Man, and Cybernetics (2014)

253 Citations

TopicMF: simultaneously exploiting ratings and reviews for recommendation

Yang Bao;Hui Fang;Jie Zhang.
national conference on artificial intelligence (2014)

245 Citations

Collaborative Security: A Survey and Taxonomy

Guozhu Meng;Yang Liu;Jie Zhang;Alexander Pokluda.
ACM Computing Surveys (2015)

245 Citations

A novel Bayesian similarity measure for recommender systems

Guibing Guo;Jie Zhang;Neil Yorke-Smith.
international joint conference on artificial intelligence (2013)

234 Citations

Merging trust in collaborative filtering to alleviate data sparsity and cold start

Guibing Guo;Jie Zhang;Daniel Thalmann.
Knowledge Based Systems (2014)

204 Citations

Best Scientists Citing Jie Zhang

Yong Cao

Yong Cao

South China University of Technology

Publications: 48

Jingjing Chang

Jingjing Chang

Xidian University

Publications: 36

Fei Huang

Fei Huang

South China University of Technology

Publications: 33

Yongsheng Chen

Yongsheng Chen

Georgia Institute of Technology

Publications: 29

Yongfang Li

Yongfang Li

Soochow University

Publications: 27

Xiangjian Wan

Xiangjian Wan

Nankai University

Publications: 26

De-gan Zhang

De-gan Zhang

Tianjin University of Technology

Publications: 23

Jishan Wu

Jishan Wu

National University of Singapore

Publications: 22

Hisao Ishibuchi

Hisao Ishibuchi

Southern University of Science and Technology

Publications: 21

Thuc-Quyen Nguyen

Thuc-Quyen Nguyen

University of California, Santa Barbara

Publications: 21

Yiwang Chen

Yiwang Chen

Nanchang University

Publications: 20

Yutaka Matsuo

Yutaka Matsuo

University of Tokyo

Publications: 20

Robin Burke

Robin Burke

University of Colorado Boulder

Publications: 20

Xiangnan He

Xiangnan He

University of Science and Technology of China

Publications: 20

Zhenhua Lin

Zhenhua Lin

Xidian University

Publications: 20

Chunyan Miao

Chunyan Miao

Nanyang Technological University

Publications: 19

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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