Chi-Yin Chow

What is he best known for?

The fields of study he is best known for:

• Artificial intelligence
• Computer network
• The Internet

The scientist’s investigation covers issues in Location-based service, Computer security, Database, Database server and Data mining. His research integrates issues of Query language, Query expansion and Web query classification, Online aggregation, Sargable in his study of Location-based service. As a part of the same scientific study, Chi-Yin Chow usually deals with the Computer security, concentrating on Snapshot and frequently concerns with Global Positioning System, Internet access and Intelligent transportation system.

As a part of the same scientific family, he mostly works in the field of Database, focusing on Anonymity and, on occasion, Server and Ranging. His Database server study frequently links to adjacent areas such as Mobile computing. His Data mining study combines topics in areas such as Feature and Information retrieval.

His most cited work include:

• The new Casper: query processing for location services without compromising privacy (970 citations)
• A peer-to-peer spatial cloaking algorithm for anonymous location-based service (435 citations)
• GeoSoCa: Exploiting Geographical, Social and Categorical Correlations for Point-of-Interest Recommendations (193 citations)

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

Chi-Yin Chow focuses on Data mining, Computer network, Location-based service, Mobile computing and Artificial intelligence. His Data mining study combines topics from a wide range of disciplines, such as Extreme learning machine, Point of interest, Feature and Histogram. The concepts of his Location-based service study are interwoven with issues in Computer security, Scalability and Database server.

Database server is a subfield of Database that Chi-Yin Chow tackles. His Mobile computing course of study focuses on Peer-to-peer and Cache invalidation. His research integrates issues of Wireless sensor network and Anonymity in his study of Server.

He most often published in these fields:

• Data mining (25.89%)
• Computer network (16.96%)
• Location-based service (15.18%)

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

• Artificial intelligence (13.39%)
• Collaborative filtering (6.25%)
• Natural language processing (4.46%)

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

Chi-Yin Chow spends much of his time researching Artificial intelligence, Collaborative filtering, Natural language processing, Encoder and Deep learning. His research investigates the connection between Collaborative filtering and topics such as Preference that intersect with issues in Multiple-criteria decision analysis and Scale. His biological study spans a wide range of topics, including Multi-task learning, Word and Cluster analysis.

He has included themes like Artificial neural network, Recurrent neural network and Data mining, Traffic prediction in his Encoder study. His work carried out in the field of Data mining brings together such families of science as Convolution and Traffic flow. His studies in Recommender system integrate themes in fields like Personalization and Machine translation.

Between 2018 and 2021, his most popular works were:

• CB-Planner: A bus line planning framework for customized bus systems (23 citations)
• STANN: A Spatio–Temporal Attentive Neural Network for Traffic Prediction (21 citations)
• STCNN: A Spatio-Temporal Convolutional Neural Network for Long-Term Traffic Prediction (11 citations)

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

• Artificial intelligence
• Computer network
• The Internet

His scientific interests lie mostly in Traffic prediction, Machine learning, Artificial intelligence, Deep learning and Recurrent neural network. The study incorporates disciplines such as Airfield traffic pattern, Traffic conditions, Convolutional neural network and Data modeling in addition to Traffic prediction. His Recurrent neural network study necessitates a more in-depth grasp of Artificial neural network.