What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Programming language
Data mining, Theoretical computer science, Graph, Null graph and Graph are his primary areas of study.
Jeffrey Xu Yu interconnects Set and Joins in the investigation of issues within Data mining.
The Theoretical computer science study combines topics in areas such as Graph partition and Algorithm, Algorithm design, Computation, Search algorithm.
The concepts of his Graph study are interwoven with issues in Time complexity and Reachability.
His research in Null graph focuses on subjects like Distance-hereditary graph, which are connected to Complement graph and Block graph.
His Graph study combines topics in areas such as RDF and Natural language, Artificial intelligence.
His most cited work include:
- Graph clustering based on structural/attribute similarities (661 citations)
- Efficient similarity joins for near duplicate detection (447 citations)
- Holistic twig joins on indexed XML documents (273 citations)
What are the main themes of his work throughout his whole career to date?
Jeffrey Xu Yu focuses on Theoretical computer science, Data mining, Graph, Information retrieval and Graph.
His Theoretical computer science research includes elements of Graph database, Graph theory, Clique-width and Null graph.
His Null graph research is multidisciplinary, relying on both Complement graph, Strength of a graph and Distance-hereditary graph.
His study in Data mining is interdisciplinary in nature, drawing from both Set and Cluster analysis, Artificial intelligence.
He usually deals with Graph and limits it to topics linked to Directed graph and Directed acyclic graph.
His Information retrieval research is multidisciplinary, incorporating perspectives in XML, Efficient XML Interchange, XML database and Database.
He most often published in these fields:
- Theoretical computer science (32.24%)
- Data mining (27.22%)
- Graph (24.13%)
What were the highlights of his more recent work (between 2016-2021)?
- Theoretical computer science (32.24%)
- Graph (24.13%)
- Vertex (7.72%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Theoretical computer science, Graph, Vertex, Graph and Artificial intelligence.
His Theoretical computer science research incorporates elements of Social network, Approximation algorithm, Heuristics, Speedup and Skyline.
His Heuristics study incorporates themes from Clique and Data mining.
Jeffrey Xu Yu combines subjects such as Time complexity, Graph theory, Computation and Scalability with his study of Graph.
Jeffrey Xu Yu has researched Graph in several fields, including Random walk and RDF.
Jeffrey Xu Yu has included themes like Pattern recognition and Natural language processing in his Artificial intelligence study.
Between 2016 and 2021, his most popular works were:
- Answering Natural Language Questions by Subgraph Matching over Knowledge Graphs (86 citations)
- Most Influential Community Search over Large Social Networks (53 citations)
- Question answering over knowledge graphs: question understanding via template decomposition (47 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Programming language
Jeffrey Xu Yu mainly focuses on Graph, Theoretical computer science, Graph, Social network and Vertex.
Many of his research projects under Graph are closely connected to Bounded function with Bounded function, tying the diverse disciplines of science together.
His Theoretical computer science research is multidisciplinary, incorporating elements of Time complexity, Scalability and Directed graph.
His Graph research integrates issues from Clique-width, RDF, Artificial intelligence and Natural language processing.
His Approximation algorithm research focuses on subjects like Heuristics, which are linked to Data mining.
His studies in Data mining integrate themes in fields like Recommender system and Benchmarking.
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