RDF packages: a scheme for efficient reasoning and querying over large-scale RDF data

被引:1
|
作者
Ohsawa, Shohei [1 ]
Amagasa, Toshiyuki [1 ]
Kitagawa, Hiroyuki [1 ]
机构
[1] Univ Tsukuba, Grad Sch Syst & Informat Engn, Tsukuba, Ibaraki, Japan
基金
日本学术振兴会;
关键词
Semantic web; RDF; RDFS reasoning;
D O I
10.1108/17440081211241969
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Purpose - The purpose of this paper is to improve the performance of querying and reasoning and querying over large-scale Resource Description Framework (RDF) data. When processing RDF(S) data, RDFS entailment is performed which often generates a large number of additional triples, which causes a poor performance. To deal with large-scale RDF data, it is important to develop a scheme which enables the processing of large RDF data in an efficient manner. Design/methodology/approach - The authors propose RDF packages, which is a space efficient format for RDF data. In an RDF package, a set of triples of the same class or triples having the same predicate are grouped into a dedicated node named Package. Any RDF data can be represented using RDF packages, and vice versa. Findings - It is found that using RDF packages can significantly reduce the size of RDF data, even after RDFS entailment. The authors experimentally evaluate the performance of the proposed scheme in terms of triple size, reasoning speed, and querying speed. Research limitations/implications - The proposed scheme is useful in processing RDF(S) data, but it needs further development to deal with an ontological language such as OWL. Originality/value - An important feature of the RDF packages is that, when performing RDFS reasoning, there is no need to modify either reasoning rules or reasoning engine; while other related schemes require reasoning rules or reasoning engine to be modified.
引用
收藏
页码:212 / +
页数:23
相关论文
共 50 条
  • [21] Querying RDF Graphs Over Partitioned Indexes
    Gai, Lei
    Liu, Junmin
    Wang, Xiaoming
    Li, Jian
    [J]. 2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD), 2017, : 2262 - 2267
  • [22] Temporal Data Representation and Querying Based on RDF
    Zhang, Fu
    Wang, Ke
    Li, Zhiyin
    Cheng, Jingwei
    [J]. IEEE ACCESS, 2019, 7 : 85000 - 85023
  • [23] Querying RDF Data with Imprecise Time Phrases
    RobatJazi, Majid
    Reformat, Marek Z.
    Pedrycz, Witold
    Musilek, Petr
    [J]. 2015 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY (WI-IAT), VOL 1, 2015, : 445 - 450
  • [24] pSPARQL: A Querying Language for Probabilistic RDF Data
    Fang, Hong
    [J]. COMPLEXITY, 2019,
  • [25] Sapphire: Querying RDF Data Made Simple
    El-Roby, Ahmed
    Ammar, Khaled
    Aboulnaga, Ashraf
    Lin, Jimmy
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2016, 9 (13): : 1481 - 1484
  • [26] A general Framework for querying Possibilistic RDF Data
    Abidi, Amna
    Bach Tobji, Mohamed Anis
    Hadjali, Allel
    Ben Yaghlane, Boutheina
    [J]. 2018 IEEE 30TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI), 2018, : 158 - 162
  • [27] Querying Fuzzy RDF Knowledge Graphs Data
    Li, Guanfeng
    Li, Weijun
    Wang, Hairong
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2020,
  • [28] A System for Querying RDF Data using LINQ
    Kumamoto, Kazumasa
    Amagasa, Toshiyuki
    Kitagawa, Hiroyuki
    [J]. PROCEEDINGS 2015 18TH INTERNATIONAL CONFERENCE ON NETWORK-BASED INFORMATION SYSTEMS (NBIS 2015), 2015, : 452 - 457
  • [29] Querying RDF Data with Text Annotated Graphs
    Han, Lushan
    Finin, Tim
    Joshi, Anupam
    Cheng, Doreen
    [J]. PROCEEDINGS OF THE 27TH INTERNATIONAL CONFERENCE ON SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT, 2015,
  • [30] Semantic Querying Big and Distributed RDF Data
    Kaoutar, Lamrani
    Abderrahim, Ghadi
    Kudagba, Florent Kunale
    [J]. PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON SMART CITY APPLICATIONS (SCA'18), 2018,