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Finding Key Structures in MMORPG Graph with Hierarchical Graph Summarization

DC Field Value Language
dc.contributor.authorJang, Jun-Gi-
dc.contributor.authorPark, Chaeheum-
dc.contributor.authorJang, Changwon-
dc.contributor.authorKim, Geonsoo-
dc.contributor.authorKang, U.-
dc.date.accessioned2022-10-17T03:51:49Z-
dc.date.available2022-10-17T03:51:49Z-
dc.date.created2022-10-07-
dc.date.issued2022-12-
dc.identifier.citationACM Transactions on Knowledge Discovery from Data, Vol.16 No.6, p. 115-
dc.identifier.issn1556-4681-
dc.identifier.urihttps://hdl.handle.net/10371/186109-
dc.description.abstractWhat are the key structures existing in a large real-world MMORPG (Massively Multiplayer Online Role-Playing Game) graph? How can we compactly summarize an MMORPG graph with hierarchical node labels, considering substructures at different levels of hierarchy? Recent MMORPGs generate complex interactions between entities inducing a heterogeneous graph where each entity has hierarchical labels. Succinctly summarizing a heterogeneous MMORPG graph is crucial to better understand its structure; however it is a challenging task since it needs to handle complex interactions and hierarchical labels efficiently. Although there exist few methods to summarize a large-scale graph, they do not deal with heterogeneous graphs with hierarchical node labels. We propose GSHL, a novel method that summarizes a heterogeneous graph with hierarchical labels. We formulate the encoding cost of hierarchical labels using MDL (Minimum Description Length). GSHL exploits the formulation to identify and segment subgraphs, and discovers compact and consistent structures in the graph. Experiments on a large real-world MMORPG graph with multi-million edges show that GSHL is a useful and scalable tool for summarizing the graph, finding important structures in the graph, and finding similar users.-
dc.language영어-
dc.publisherSpecial Interest Group on Computer Graphics, Association for Computing Machinery-
dc.titleFinding Key Structures in MMORPG Graph with Hierarchical Graph Summarization-
dc.typeArticle-
dc.identifier.doi10.1145/3522691-
dc.citation.journaltitleACM Transactions on Knowledge Discovery from Data-
dc.identifier.wosid000859375300015-
dc.citation.number6-
dc.citation.startpage115-
dc.citation.volume16-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorKang, U.-
dc.type.docTypeArticle-
dc.description.journalClass1-
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