J
Jinha Kim
Researcher at Pohang University of Science and Technology
Publications - 29
Citations - 1072
Jinha Kim is an academic researcher from Pohang University of Science and Technology. The author has contributed to research in topics: Maximization & Skyline. The author has an hindex of 14, co-authored 26 publications receiving 960 citations. Previous affiliations of Jinha Kim include Business International Corporation & Oracle Corporation.
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Proceedings ArticleDOI
TurboGraph: a fast parallel graph engine handling billion-scale graphs in a single PC
TL;DR: This paper proposes a general, disk-based graph engine called TurboGraph to process billion-scale graphs very efficiently by using modern hardware on a single PC and proposes a novel parallel execution model, called pin-and-slide, which is the first truly parallel graph engine that exploits full parallelism including multi-core parallelism and FlashSSD IO parallelism.
Proceedings ArticleDOI
Scalable and parallelizable processing of influence maximization for large-scale social networks?
TL;DR: A scalable influence approximation algorithm, Independent Path Algorithm (IPA) for Independent Cascade (IC) diffusion model, which efficiently approximates influence by considering an independent influence path as an influence evaluation unit and is implemented in the demo application for influence maximization.
Proceedings ArticleDOI
PGQL: a property graph query language
TL;DR: A new query language for the popular Property Graph (PG) data model: the Property Graph Query Language (PGQL), based on the paradigm of graph pattern matching, closely follows syntactic structures of SQL, and provides regular path queries with conditions on labels and properties to allow for reachability and path finding queries.
Proceedings ArticleDOI
Parallel Skyline Computation on Multicore Architectures
TL;DR: This paper compares two parallel skyline algorithms: a parallel version of the branch-and-bound algorithm (BBS) and a new parallel algorithm based on skeletal parallel programming, which is comparable to parallel BBS in speed.
Proceedings ArticleDOI
Taming subgraph isomorphism for RDF query processing
TL;DR: TurboHOM++ as discussed by the authors is based on the state-of-the-art subgraph isomorphism algorithm, which is tamed for the RDF processing, and compare it with the representative RDF Processing engines for several RDF benchmarks in a server machine where billions of triples can be loaded in memory.