What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Computer network
His scientific interests lie mostly in Data mining, Mobile computing, Social network, Distributed computing and Information retrieval.
The concepts of his Data mining study are interwoven with issues in Search engine, Set, Cluster analysis, Heuristics and Point.
Wang-Chien Lee interconnects Wireless, Location-based service, Mobile search, Search engine indexing and Mobile database in the investigation of issues within Mobile computing.
His Social network study combines topics from a wide range of disciplines, such as Social influence, Recommender system and Preference.
His studies deal with areas such as Cache algorithms, Cache invalidation, Computer network, Cache and Cache coloring as well as Distributed computing.
His work in Information retrieval addresses subjects such as Point of interest, which are connected to disciplines such as Volunteered geographic information, Temporal database, Schema and Naive Bayes classifier.
His most cited work include:
- Exploiting geographical influence for collaborative point-of-interest recommendation (775 citations)
- Location recommendation for location-based social networks (368 citations)
- Prediction-based strategies for energy saving in object tracking sensor networks (277 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Data mining, Computer network, Distributed computing, Information retrieval and Search engine indexing.
His Data mining study incorporates themes from Wireless sensor network, Spatial database, Set and k-nearest neighbors algorithm.
His study in Computer network is interdisciplinary in nature, drawing from both Wireless network and Database.
As part of his studies on Distributed computing, Wang-Chien Lee frequently links adjacent subjects like Scalability.
He is studying Search engine, which is a component of Information retrieval.
His work deals with themes such as Wireless and Mobile search, which intersect with Mobile computing.
He most often published in these fields:
- Data mining (26.12%)
- Computer network (17.94%)
- Distributed computing (13.19%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (11.08%)
- Data mining (26.12%)
- Machine learning (7.12%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Data mining, Machine learning, Social network and Theoretical computer science are his primary areas of study.
His research integrates issues of Approximation algorithm and Pattern recognition in his study of Artificial intelligence.
His Data mining research includes themes of Point, Cluster analysis, Segmentation and Imputation.
His biological study spans a wide range of topics, including Graph, Analytics and Benchmark.
His Social network research integrates issues from Social influence, Clustering coefficient, Addiction and Time complexity.
Wang-Chien Lee has included themes like Quality, Feature learning, Set and Group in his Theoretical computer science study.
Between 2014 and 2021, his most popular works were:
- HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning (232 citations)
- Clustering and aggregating clues of trajectories for mining trajectory patterns and routes (109 citations)
- Semantic Annotation of Mobility Data using Social Media (51 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Computer network
Wang-Chien Lee spends much of his time researching Artificial intelligence, Data mining, Social network, Machine learning and World Wide Web.
His work on Artificial neural network, Regularization and Text corpus is typically connected to Tera- as part of general Artificial intelligence study, connecting several disciplines of science.
Wang-Chien Lee works in the field of Data mining, focusing on Aggregate in particular.
Wang-Chien Lee works mostly in the field of Social network, limiting it down to topics relating to Addiction and, in certain cases, Intervention and The Internet.
His research investigates the connection between Machine learning and topics such as Theoretical computer science that intersect with problems in Pruning, Query optimization, Integer programming, Impromptu and Set.
Wang-Chien Lee combines subjects such as Test and Pearson product-moment correlation coefficient with his study of World Wide Web.
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