H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 67 Citations 20,664 358 World Ranking 1023 National Ranking 94

Research.com Recognitions

Awards & Achievements

2019 - ACM Distinguished Member

2019 - ACM Senior Member

2019 - IEEE Fellow For contributions to the theory and applications of machine learning in social computing

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary scientific interests are in Artificial intelligence, Information retrieval, Machine learning, Recommender system and Data mining. His Artificial intelligence study combines topics in areas such as Computation, Body of knowledge, Minimax and Pattern recognition. His Information retrieval study incorporates themes from Ranking, Field and Language model.

Machine learning and Set are frequently intertwined in his study. The concepts of his Recommender system study are interwoven with issues in Matrix decomposition, Web application, Probabilistic logic and Social network. His work deals with themes such as Constraint, Binary classification, Support vector machine and Blossom algorithm, which intersect with Data mining.

His most cited work include:

  • Recommender systems with social regularization (1135 citations)
  • SoRec: social recommendation using probabilistic matrix factorization (992 citations)
  • Learning to recommend with social trust ensemble (662 citations)

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

His main research concerns Artificial intelligence, Machine learning, Information retrieval, Data mining and World Wide Web. The study incorporates disciplines such as Natural language processing, Recommender system and Pattern recognition in addition to Artificial intelligence. The various areas that Irwin King examines in his Recommender system study include Matrix decomposition and Social network.

His studies deal with areas such as Classifier, Training set, Image retrieval and Minimax as well as Machine learning. In his study, Ranking is strongly linked to Ranking, which falls under the umbrella field of Information retrieval. Irwin King combines topics linked to Data science with his work on World Wide Web.

He most often published in these fields:

  • Artificial intelligence (45.60%)
  • Machine learning (24.38%)
  • Information retrieval (17.16%)

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

  • Artificial intelligence (45.60%)
  • Natural language processing (6.77%)
  • Machine learning (24.38%)

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

His primary areas of study are Artificial intelligence, Natural language processing, Machine learning, Theoretical computer science and Graph. The Artificial intelligence study combines topics in areas such as Quality and Generalization. His Natural language processing research integrates issues from Word, Logical consequence and Conversation.

His research in Machine learning is mostly concerned with Semi-supervised learning. Irwin King combines subjects such as Field and Taxonomy with his study of Semi-supervised learning. His work in Theoretical computer science tackles topics such as Graph which are related to areas like Cold start, Matrix completion and Recommender system.

Between 2018 and 2021, his most popular works were:

  • Title-Guided Encoding for Keyphrase Generation (41 citations)
  • MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding (39 citations)
  • STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems (23 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of investigation include Artificial intelligence, Machine learning, Natural language processing, Generative grammar and Theoretical computer science. His Artificial intelligence research is multidisciplinary, incorporating elements of Quality, Dialog box and Code. His study on Overfitting is often connected to Medical diagnosis as part of broader study in Machine learning.

His Natural language processing study also includes fields such as

  • Social media which intersects with area such as Salient,
  • Word and related Encoding, Range, Encoder, Margin and Set. His Generative grammar research incorporates elements of Semi-supervised learning, Toolbox, Support vector machine, Unsupervised learning and Supervised learning. His work carried out in the field of Theoretical computer science brings together such families of science as Recommender system, Graph neural networks, Matrix completion, Graph embedding and Cold start.

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

Recommender systems with social regularization

Hao Ma;Dengyong Zhou;Chao Liu;Michael R. Lyu.
web search and data mining (2011)

1436 Citations

SoRec: social recommendation using probabilistic matrix factorization

Hao Ma;Haixuan Yang;Michael R. Lyu;Irwin King.
conference on information and knowledge management (2008)

1302 Citations

Learning to recommend with social trust ensemble

Hao Ma;Irwin King;Michael R. Lyu.
international acm sigir conference on research and development in information retrieval (2009)

877 Citations

QoS-Aware Web Service Recommendation by Collaborative Filtering

Zibin Zheng;Hao Ma;M R Lyu;I King.
IEEE Transactions on Services Computing (2011)

719 Citations

Effective missing data prediction for collaborative filtering

Hao Ma;Irwin King;Michael R. Lyu.
international acm sigir conference on research and development in information retrieval (2007)

566 Citations

Fused matrix factorization with geographical and social influence in location-based social networks

Chen Cheng;Haiqin Yang;Irwin King;Michael R. Lyu.
national conference on artificial intelligence (2012)

557 Citations

A Survey of Crowdsourcing Systems

Man-Ching Yuen;Irwin King;Kwong-Sak Leung.
privacy security risk and trust (2011)

503 Citations

WSRec: A Collaborative Filtering Based Web Service Recommender System

Zibin Zheng;Hao Ma;Michael R. Lyu;Irwin King.
international conference on web services (2009)

502 Citations

Where you like to go next: successive point-of-interest recommendation

Chen Cheng;Haiqin Yang;Michael R. Lyu;Irwin King.
international joint conference on artificial intelligence (2013)

421 Citations

Collaborative Web Service QoS Prediction via Neighborhood Integrated Matrix Factorization

Zibin Zheng;Hao Ma;M. R. Lyu;Irwin King.
IEEE Transactions on Services Computing (2013)

364 Citations

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Best Scientists Citing Irwin King

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Michael R. Lyu

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Michigan State University

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Singapore Management University

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Hongzhi Yin

University of Queensland

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Xiaofang Zhou

Xiaofang Zhou

Hong Kong University of Science and Technology

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Hong Kong University of Science and Technology

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Chuan Shi

Chuan Shi

Beijing University of Posts and Telecommunications

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University of Technology Sydney

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Hui Xiong

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Rutgers, The State University of New Jersey

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Jiawei Han

Jiawei Han

University of Illinois at Urbana-Champaign

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Xing Xie

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