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 27,994 144 World Ranking 3270 National Ranking 1700

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Machine learning

His main research concerns Recommender system, Data mining, Personalization, Data science and Knowledge extraction. As a part of the same scientific family, he mostly works in the field of Recommender system, focusing on Process and, on occasion, Focus. His Data mining study combines topics in areas such as Customer lifetime value, Customer relationship management, Management science and Leverage.

His research investigates the link between Personalization and topics such as Profiling that cross with problems in User profile and One-to-one. The various areas that he examines in his Knowledge extraction study include Structure, Machine learning and Management system. To a larger extent, Alexander Tuzhilin studies Information retrieval with the aim of understanding Collaborative filtering.

His most cited work include:

  • Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions (7869 citations)
  • Context-Aware Recommender Systems (1238 citations)
  • Incorporating contextual information in recommender systems using a multidimensional approach (1034 citations)

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

Alexander Tuzhilin focuses on Recommender system, Data mining, Artificial intelligence, Information retrieval and Data science. His Recommender system study incorporates themes from Process and Personalization. His study in Data mining is interdisciplinary in nature, drawing from both Market segmentation and Temporal logic.

His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Natural language processing. Alexander Tuzhilin works in the field of Information retrieval, namely Query language. Alexander Tuzhilin studied Data science and Knowledge extraction that intersect with Structure.

He most often published in these fields:

  • Recommender system (37.50%)
  • Data mining (28.24%)
  • Artificial intelligence (20.83%)

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

  • Recommender system (37.50%)
  • Artificial intelligence (20.83%)
  • Machine learning (12.96%)

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

The scientist’s investigation covers issues in Recommender system, Artificial intelligence, Machine learning, Information retrieval and Deep learning. His Recommender system research is multidisciplinary, incorporating elements of Data science, Variety and Process. Alexander Tuzhilin combines subjects such as Domain, Event, Pattern recognition and Natural language processing with his study of Artificial intelligence.

His Machine learning study integrates concerns from other disciplines, such as Sentence, Quality and Personalization. His Deep learning research incorporates themes from Loan, Finance and Collaborative filtering. His Collaborative filtering research is multidisciplinary, incorporating perspectives in Algorithm and Simple.

Between 2017 and 2021, his most popular works were:

  • DDTCDR: Deep Dual Transfer Cross Domain Recommendation (13 citations)
  • E.T.-RNN: Applying Deep Learning to Credit Loan Applications (13 citations)
  • Recommending Remedial Learning Materials to Students by Filling Their Knowledge Gaps (11 citations)

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

  • Artificial intelligence
  • Programming language
  • Machine learning

Alexander Tuzhilin spends much of his time researching Recommender system, Information retrieval, Artificial intelligence, Deep learning and Collaborative filtering. Alexander Tuzhilin integrates Recommender system with Performance results in his research. The Information retrieval study combines topics in areas such as Transfer of learning, Feature, Autoencoder and DUAL.

His Artificial intelligence research focuses on subjects like Machine learning, which are linked to Quality, Sentence and Personalization. His Deep learning study incorporates themes from Loan, Finance, Process and Domain. His Collaborative filtering study frequently involves adjacent topics like Feature vector.

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

Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

G. Adomavicius;A. Tuzhilin.
IEEE Transactions on Knowledge and Data Engineering (2005)

12637 Citations

Context-Aware Recommender Systems

Gediminas Adomavicius;Bamshad Mobasher;Francesco Ricci;Alexander Tuzhilin.
Ai Magazine (2011)

2620 Citations

Incorporating contextual information in recommender systems using a multidimensional approach

Gediminas Adomavicius;Ramesh Sankaranarayanan;Shahana Sen;Alexander Tuzhilin.
ACM Transactions on Information Systems (2005)

1580 Citations

System and method for dynamic profiling of users in one-to-one applications

Alexander S. Tuzhilin;Gediminas Adomavicius.
(1997)

1058 Citations

What makes patterns interesting in knowledge discovery systems

A. Silberschatz;A. Tuzhilin.
IEEE Transactions on Knowledge and Data Engineering (1996)

1032 Citations

On subjective measures of interestingness in knowledge discovery

Avi Silberschatz;Alexander Tuzhilin.
knowledge discovery and data mining (1995)

573 Citations

Personalization technologies: a process-oriented perspective

Gediminas Adomavicius;Alexander Tuzhilin.
Communications of The ACM (2005)

496 Citations

Using data mining methods to build customer profiles

G. Adomavicius;A. Tuzhilin.
IEEE Computer (2001)

415 Citations

An energy-efficient mobile recommender system

Yong Ge;Hui Xiong;Alexander Tuzhilin;Keli Xiao.
knowledge discovery and data mining (2010)

388 Citations

The long tail of recommender systems and how to leverage it

Yoon-Joo Park;Alexander Tuzhilin.
conference on recommender systems (2008)

385 Citations

Best Scientists Citing Alexander Tuzhilin

Francesco Ricci

Francesco Ricci

Free University of Bozen-Bolzano

Publications: 78

Xing Xie

Xing Xie

Microsoft (United States)

Publications: 56

Dietmar Jannach

Dietmar Jannach

University of Klagenfurt

Publications: 50

Robin Burke

Robin Burke

University of Colorado Boulder

Publications: 48

Hui Xiong

Hui Xiong

Rutgers, The State University of New Jersey

Publications: 47

Tao Zhou

Tao Zhou

University of Electronic Science and Technology of China

Publications: 47

Bamshad Mobasher

Bamshad Mobasher

DePaul University

Publications: 47

Xin Luo

Xin Luo

Chinese Academy of Sciences

Publications: 47

Adam Soroca

Adam Soroca

Millennial Media LLC

Publications: 40

Jie Lu

Jie Lu

University of Technology Sydney

Publications: 39

Pablo Castells

Pablo Castells

Autonomous University of Madrid

Publications: 38

Jorey Ramer

Jorey Ramer

Super Home Inc.

Publications: 38

Dennis Doughty

Dennis Doughty

Lola Travel Company Inc

Publications: 38

Yi-Cheng Zhang

Yi-Cheng Zhang

University of Fribourg

Publications: 37

Iván Cantador

Iván Cantador

Autonomous University of Madrid

Publications: 36

Bing Liu

Bing Liu

Peking University

Publications: 35

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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