On Statistical Characteristics of Real-Life Knowledge Graphs

Autor:	Chengyu Wang, Aoying Zhou, Weining Qian, Bing Xiao, Wenliang Cheng
Rok vydání:	2016
Předmět:	Graph database Theoretical computer science Knowledge graph Social network Computer science business.industry Existential quantification Management system Benchmark (computing) Natural (music) computer.software_genre business computer
Zdroj:	Big Data Benchmarks, Performance Optimization, and Emerging Hardware ISBN: 9783319290058 BPOE
DOI:	10.1007/978-3-319-29006-5_4
Popis:	The success of open-access knowledge graphs, such as YAGO, and commercial products, such as Google Knowledge Graph, has attracted much attention from both academic and industrial communities in building common-sense and domain-specific knowledge graphs. A natural question arises that how to effectively and efficiently manage a large-scale knowledge graph. Though systems and technologies that use relational storage engines or native graph database management systems are proposed, there exists no widely accepted solution. Therefore, a benchmark for management of knowledge graphs is required.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d4287037f0530b9cf2003b5481af7a24 https://doi.org/10.1007/978-3-319-29006-5_4 Zobrazit plný text záznamu