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.
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.
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.
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.
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.
Graph clustering based on structural/attribute similarities
Yang Zhou;Hong Cheng;Jeffrey Xu Yu.
very large data bases (2009)
Efficient similarity joins for near-duplicate detection
Chuan Xiao;Wei Wang;Xuemin Lin;Jeffrey Xu Yu.
ACM Transactions on Database Systems (2011)
Efficient similarity joins for near duplicate detection
Chuan Xiao;Wei Wang;Xuemin Lin;Jeffrey Xu Yu.
the web conference (2008)
Holistic twig joins on indexed XML documents
Haifeng Jiang;Wei Wang;Hongjun Lu;Jeffrey Xu Yu.
very large data bases (2003)
Efficient computation of the skyline cube
Yidong Yuan;Xuemin Lin;Qing Liu;Wei Wang.
very large data bases (2005)
Taming verification hardness: an efficient algorithm for testing subgraph isomorphism
Haichuan Shang;Ying Zhang;Xuemin Lin;Jeffrey Xu Yu.
very large data bases (2008)
Finding time-dependent shortest paths over large graphs
Bolin Ding;Jeffrey Xu Yu;Lu Qin.
extending database technology (2008)
Dual Labeling: Answering Graph Reachability Queries in Constant Time
Haixun Wang;Hao He;Jun Yang;P.S. Yu.
international conference on data engineering (2006)
Graph indexing: tree + delta <= graph
Peixiang Zhao;Jeffrey Xu Yu;Philip S. Yu.
very large data bases (2007)
Condensed cube: an effective approach to reducing data cube size
Wei Wang;Jianlin Feng;Hongjun Lu;J.X. Yu.
international conference on data engineering (2002)
Profile was last updated on December 6th, 2021.
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