What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- Computer network
Ming-Syan Chen spends much of his time researching Data mining, Association rule learning, Artificial intelligence, Computer network and Real-time computing.
His Data mining research is multidisciplinary, incorporating perspectives in Path, Hash function, Database and Search algorithm.
His Database study combines topics in areas such as Query expansion and The Internet.
His studies in Association rule learning integrate themes in fields like Database transaction, Transaction processing, Temporal database and Database theory.
His Artificial intelligence research integrates issues from Machine learning, Computer vision and Pattern recognition.
His Computer network research is multidisciplinary, incorporating elements of Wireless and Communication channel.
His most cited work include:
- Data mining: an overview from a database perspective (1894 citations)
- An effective hash-based algorithm for mining association rules (1398 citations)
- Efficient data mining for path traversal patterns (505 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Data mining, Artificial intelligence, Distributed computing, Computer network and Mobile computing.
His work deals with themes such as Database transaction, Database and Cluster analysis, which intersect with Data mining.
Ming-Syan Chen studied Artificial intelligence and Machine learning that intersect with Social network.
His work carried out in the field of Distributed computing brings together such families of science as Node, Scalability and Server.
His Computer network research incorporates elements of Wireless and Communication channel.
His study in Mobile computing is interdisciplinary in nature, drawing from both Mobile search and Mobile database.
He most often published in these fields:
- Data mining (29.67%)
- Artificial intelligence (21.34%)
- Distributed computing (15.65%)
What were the highlights of his more recent work (between 2012-2021)?
- Artificial intelligence (21.34%)
- Social network (7.93%)
- Machine learning (10.57%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Social network, Machine learning, Data mining and Maximization are his primary areas of study.
His Artificial intelligence research is multidisciplinary, relying on both Group and Pattern recognition.
His work in Social network addresses subjects such as Internet privacy, which are connected to disciplines such as Anonymity.
Ming-Syan Chen is studying Big data, which is a component of Data mining.
His Maximization study incorporates themes from Greedy algorithm and Viral marketing.
His Cluster analysis research includes elements of Spatial multiplexing, Visualization, Distributed computing and 3G MIMO.
Between 2012 and 2021, his most popular works were:
- Video Event Detection by Inferring Temporal Instance Labels (100 citations)
- Predicting Winning Price in Real Time Bidding with Censored Data (54 citations)
- Sample-Specific Late Fusion for Visual Category Recognition (53 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- The Internet
Ming-Syan Chen mainly investigates Artificial intelligence, Data mining, Machine learning, Social network and Cloud computing.
The various areas that Ming-Syan Chen examines in his Artificial intelligence study include Ranking, Function and Pattern recognition.
His Data mining research overlaps with Computational biology, Nucleotide Motif, Amino Acid Motifs, Systems biology and Computational genomics.
His study in the fields of Pruning under the domain of Machine learning overlaps with other disciplines such as Variable.
His studies deal with areas such as Distributed computing and Big data as well as Cloud computing.
His biological study spans a wide range of topics, including Node, Pipeline, Broadcasting and Upload.
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