R
Reynold Cheng
Researcher at University of Hong Kong
Publications - 192
Citations - 8947
Reynold Cheng is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Uncertain data & Probabilistic logic. The author has an hindex of 44, co-authored 188 publications receiving 7717 citations. Previous affiliations of Reynold Cheng include University of New South Wales & Hong Kong Polytechnic University.
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Journal ArticleDOI
On link-based similarity join
TL;DR: This paper proposes link-based similarity join (LS-join), which extends the similarity join operator to link- based measures, and improves the solutions for PPR and SR, which involve expensive random-walk operations.
Proceedings ArticleDOI
Change tolerant indexing for constantly evolving data
TL;DR: This paper proposes an index structure explicitly designed to perform well for both querying and updating, and observes that objects often stay in a region for an extended amount of time, and exploits this phenomenon to optimize an index for both updates and queries.
Journal ArticleDOI
An Indexing Framework for Queries on Probabilistic Graphs
TL;DR: The ProbTree is a data structure that stores a succinct, or indexed, version of the possible worlds of the graph, and lossless and lossy methods for generating the ProbTree are examined, which reflect the tradeoff between the accuracy and efficiency of query evaluation.
Journal ArticleDOI
On Minimal Steiner Maximum-Connected Subgraph Queries
TL;DR: The minimal SMCS is investigated, which is the minimal subgraph of the inline-formula-based Expand-Refine algorithms, as well as their approximate versions with accuracy guarantees and a cache-based processing model to improve the efficiency for an important case when the largest connectivity is needed.
Journal Article
Location Privacy in Moving-Object Environments
TL;DR: This paper proposes a framework for preserving location privacy in moving-object environments based on the idea of sending to the service provider suitably modified location information, which achieves privacy without degrading service quality.