Ying Zhang mostly deals with Data mining, Theoretical computer science, Object, Search engine indexing and Graph. His work carried out in the field of Data mining brings together such families of science as Data modeling, Spatial query, Set and k-nearest neighbors algorithm. His Theoretical computer science study which covers Computation that intersects with Combinatorics, Core and Similarity.
His Search engine indexing research includes themes of Nearest neighbor search and Database. His study on Subgraph isomorphism problem is often connected to Modular decomposition, Quality and Point as part of broader study in Graph. His Skyline study integrates concerns from other disciplines, such as Time complexity and Dynamic programming, Mathematical optimization, Approximation algorithm.
His main research concerns Theoretical computer science, Data mining, Graph, Set and Vertex. He works mostly in the field of Theoretical computer science, limiting it down to concerns involving Pruning and, occasionally, Location-based service. Ying Zhang combines subjects such as Object, Spatial query, Search engine indexing and k-nearest neighbors algorithm with his study of Data mining.
His Graph research is multidisciplinary, incorporating elements of Graph and Computation. The various areas that Ying Zhang examines in his Set study include Ranking, Synthetic data, Containment and Skyline. His work focuses on many connections between Vertex and other disciplines, such as Time complexity, that overlap with his field of interest in Mathematical optimization.
Ying Zhang mainly investigates Theoretical computer science, Vertex, Graph, Bipartite graph and Algorithm. Ying Zhang interconnects Scalability, Graph, Power graph analysis and Pruning in the investigation of issues within Theoretical computer science. He combines subjects such as Time complexity, Computation, Core and Social network with his study of Vertex.
His Graph research includes elements of Artificial neural network, Reachability, Search engine indexing and Index. The concepts of his Algorithm study are interwoven with issues in Precision and recall, Nearest neighbor search, Curse of dimensionality and k-nearest neighbors algorithm. His study looks at the relationship between Nearest neighbor search and topics such as Metric space, which overlap with Data mining.
Graph, Vertex, Combinatorics, Computation and Speedup are his primary areas of study. His Graph study incorporates themes from Set and Information retrieval, Search engine indexing. His studies in Set integrate themes in fields like Property and Signed graph.
His study on Vertex also encompasses disciplines like
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Selecting Stars: The k Most Representative Skyline Operator
Xuemin Lin;Yidong Yuan;Qing Zhang;Ying Zhang.
international conference on data engineering (2007)
Taming verification hardness: an efficient algorithm for testing subgraph isomorphism
Haichuan Shang;Ying Zhang;Xuemin Lin;Jeffrey Xu Yu.
very large data bases (2008)
Inverted Linear Quadtree: Efficient Top K Spatial Keyword Search
Chengyuan Zhang;Ying Zhang;Wenjie Zhang;Xuemin Lin.
IEEE Transactions on Knowledge and Data Engineering (2016)
Approximate Nearest Neighbor Search on High Dimensional Data — Experiments, Analyses, and Improvement
Wen Li;Ying Zhang;Yifang Sun;Wei Wang.
IEEE Transactions on Knowledge and Data Engineering (2020)
Probabilistic skyline operator over sliding windows
Wenjie Zhang;Xuemin Lin;Ying Zhang;Wei Wang.
Information Systems (2013)
Probabilistic Skyline Operator over Sliding Windows
Wenjie Zhang;Xuemin Lin;Ying Zhang;Wei Wang.
international conference on data engineering (2009)
Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks
Muhammad Aamir Cheema;Wenjie Zhang;Xuemin Lin;Ying Zhang.
very large data bases (2012)
A survey of community search over big graphs
Yixiang Fang;Xin Huang;Lu Qin;Ying Zhang.
very large data bases (2020)
Influence zone: Efficiently processing reverse k nearest neighbors queries
Muhammad Aamir Cheema;Xuemin Lin;Wenjie Zhang;Ying Zhang.
international conference on data engineering (2011)
SRS: solving c-approximate nearest neighbor queries in high dimensional euclidean space with a tiny index
Yifang Sun;Wei Wang;Jianbin Qin;Ying Zhang.
very large data bases (2014)
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