Performance analysis and comparison for linked data index structure

Sun Yu Xiang; Yongju Lee

doi:10.17654/HMSI118071

Performance analysis and comparison for linked data index structure

Sun Yu Xiang, Yongju Lee

Kyungpook National University

Research output: Contribution to journal › Article › peer-review

Abstract

With the development of semantic web and the rapid growth of data volume of RDF, the storage and retrieval of the large-scale RDF data have become a research hotspot. Therefore, it is an important issue how to the large-scale RDF data are stored, indexed, and queried. In this paper, we present a solution to store and query the large-scale RDF data by k-d tree and R*-tree, and analyze the strength and weakness of both techniques. We also propose an optimized scheme focus on the join query for adapting R*-tree.

Original language	English
Pages (from-to)	71-76
Number of pages	6
Journal	JP Journal of Heat and Mass Transfer
Volume	15
Issue number	Special Issue 1
DOIs	https://doi.org/10.17654/HMSI118071
State	Published - Jun 2018

Keywords

DBpedia
K-d tree
Linked data
R*-tree
RDF
Semantic web
SPARQL

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10.17654/HMSI118071

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title = "Performance analysis and comparison for linked data index structure",

abstract = "With the development of semantic web and the rapid growth of data volume of RDF, the storage and retrieval of the large-scale RDF data have become a research hotspot. Therefore, it is an important issue how to the large-scale RDF data are stored, indexed, and queried. In this paper, we present a solution to store and query the large-scale RDF data by k-d tree and R*-tree, and analyze the strength and weakness of both techniques. We also propose an optimized scheme focus on the join query for adapting R*-tree.",

keywords = "DBpedia, K-d tree, Linked data, R*-tree, RDF, Semantic web, SPARQL",

author = "Xiang, {Sun Yu} and Yongju Lee",

note = "Publisher Copyright: {\textcopyright} 2018 Pushpa Publishing House, Allahabad, India.",

year = "2018",

month = jun,

doi = "10.17654/HMSI118071",

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T1 - Performance analysis and comparison for linked data index structure

AU - Xiang, Sun Yu

AU - Lee, Yongju

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AB - With the development of semantic web and the rapid growth of data volume of RDF, the storage and retrieval of the large-scale RDF data have become a research hotspot. Therefore, it is an important issue how to the large-scale RDF data are stored, indexed, and queried. In this paper, we present a solution to store and query the large-scale RDF data by k-d tree and R*-tree, and analyze the strength and weakness of both techniques. We also propose an optimized scheme focus on the join query for adapting R*-tree.

KW - DBpedia

KW - K-d tree

KW - Linked data

KW - R-tree

KW - RDF

KW - Semantic web

KW - SPARQL

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M3 - Article

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VL - 15

SP - 71

EP - 76

JO - JP Journal of Heat and Mass Transfer

JF - JP Journal of Heat and Mass Transfer

IS - Special Issue 1

ER -

Performance analysis and comparison for linked data index structure

Abstract

Keywords

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