H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 36 Citations 4,825 279 World Ranking 5638 National Ranking 14

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Data mining

His main research concerns Data mining, Database transaction, Efficient algorithm, Scalability and Pruning. He integrates Data mining and Execution time in his research. His studies deal with areas such as Space, Computation and Field as well as Database transaction.

His Scalability research is multidisciplinary, incorporating perspectives in Knowledge extraction, Skyline and Pattern recognition. As a member of one scientific family, Jerry Chun-Wei Lin mostly works in the field of Pruning, focusing on Measure and, on occasion, Timestamp. The study incorporates disciplines such as Machine learning and Fast algorithm in addition to Artificial intelligence.

His most cited work include:

  • The SPMF Open-Source Data Mining Library Version 2 (218 citations)
  • A survey of itemset mining (100 citations)
  • EFIM: A Highly Efficient Algorithm for High-Utility Itemset Mining (80 citations)

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

Data mining, Pruning, Database transaction, Artificial intelligence and Structure are his primary areas of study. He undertakes interdisciplinary study in the fields of Data mining and Speedup through his works. Jerry Chun-Wei Lin combines subjects such as Field, Uncertain data and Sequential Pattern Mining with his study of Pruning.

When carried out as part of a general Database transaction research project, his work on Utility mining is frequently linked to work in Profit, therefore connecting diverse disciplines of study. His work deals with themes such as Natural language processing, Machine learning and Pattern recognition, which intersect with Artificial intelligence. Jerry Chun-Wei Lin incorporates Projection and Extension in his research.

He most often published in these fields:

  • Data mining (62.61%)
  • Pruning (23.71%)
  • Database transaction (21.28%)

What were the highlights of his more recent work (between 2020-2021)?

  • Artificial intelligence (19.15%)
  • Data mining (62.61%)
  • Pruning (23.71%)

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

His scientific interests lie mostly in Artificial intelligence, Data mining, Pruning, Database transaction and Artificial neural network. His research integrates issues of Natural language processing, Machine learning and Pattern recognition in his study of Artificial intelligence. His work on Knowledge extraction as part of general Data mining research is frequently linked to Graph based, thereby connecting diverse disciplines of science.

Jerry Chun-Wei Lin interconnects Affinity analysis, Space, Field and Fuzzy logic in the investigation of issues within Pruning. His Database transaction research integrates issues from Computer cluster, Information sensitivity and Information privacy. Jerry Chun-Wei Lin has included themes like Tree and Tree structure in his Scalability study.

Between 2020 and 2021, his most popular works were:

  • A Survey of Utility-Oriented Pattern Mining (47 citations)
  • ASRNN: A recurrent neural network with an attention model for sequence labeling (18 citations)
  • ASRNN: A recurrent neural network with an attention model for sequence labeling (18 citations)

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

  • Artificial intelligence
  • Machine learning
  • Algorithm

His main research concerns Artificial intelligence, Deep learning, Data mining, Sharpe ratio and Artificial neural network. His work investigates the relationship between Artificial intelligence and topics such as Pattern recognition that intersect with problems in Sequence labeling. His Deep learning study also includes

  • Cluster analysis that connect with fields like Object detection, Feature extraction, Convolutional neural network and Particle swarm optimization,
  • Anomaly detection and related Convolution and Knowledge extraction.

His biological study spans a wide range of topics, including Field and Pruning. His Artificial neural network research includes themes of Named-entity recognition, Parsing, Chunking and Conditional random field. His Machine learning research is multidisciplinary, incorporating elements of Human behavior and Differential evolution.

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.

Top Publications

The SPMF Open-Source Data Mining Library Version 2

Philippe Fournier-Viger;Jerry Chun-Wei Lin;Antonio Gomariz;Ted Gueniche.
european conference on machine learning (2016)

302 Citations

A survey of itemset mining

Philippe Fournier‐Viger;Jerry Chun‐Wei Lin;Bay Vo;Bay Vo;Tin Truong Chi.
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (2017)

153 Citations

EFIM: a fast and memory efficient algorithm for high-utility itemset mining

Souleymane Zida;Philippe Fournier-Viger;Jerry Chun-Wei Lin;Cheng-Wei Wu.
Knowledge and Information Systems (2017)

116 Citations

EFIM: A Highly Efficient Algorithm for High-Utility Itemset Mining

Souleymane Zida;Philippe Fournier-Viger;Jerry Chun Wei Lin;Cheng Wei Wu.
mexican international conference on artificial intelligence (2015)

112 Citations

Security and Privacy Techniques in IoT Environment.

Jerry Chun-Wei Lin;Kuo-Hui Yeh.
Sensors (2020)

101 Citations

Efficient algorithms for mining high-utility itemsets in uncertain databases

Jerry Chun-Wei Lin;Wensheng Gan;Philippe Fournier-Viger;Tzung-Pei Hong.
Knowledge Based Systems (2016)

85 Citations

A survey of incremental high-utility itemset mining

Wensheng Gan;Jerry Chun-Wei Lin;Philippe Fournier-Viger;Han-Chieh Chao.
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (2018)

85 Citations

A Survey of Parallel Sequential Pattern Mining

Wensheng Gan;Jerry Chun-Wei Lin;Philippe Fournier-Viger;Han-Chieh Chao.
ACM Transactions on Knowledge Discovery From Data (2019)

76 Citations

An ACO-based approach to mine high-utility itemsets

Jimmy Ming-Tai Wu;Justin Zhan;Jerry Chun-Wei Lin.
Knowledge Based Systems (2017)

75 Citations

Efficient algorithms for mining up-to-date high-utility patterns

Jerry Chun-Wei Lin;Wensheng Gan;Tzung-Pei Hong;Vincent S. Tseng.
Advanced Engineering Informatics (2015)

73 Citations

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

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