A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics

Shibata Yuta; Masaomi Kimura; Toba Yuki

doi:10.1109/ISCSIC.2017.44

A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics

Shibata Yuta, Masaomi Kimura, Toba Yuki

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A topic map has composed a topic expressing concepts, an association between the concepts and a role of association. A topic map database is currently existed to be utilized to a system. The existing Topic map database (TMDB) uses a system such as relational database and object oriented database, and it was necessary to convert from the structure of each system to a topic map structure. Therefore, we propose a native TMDB management system that can store and manipulate data without changing the data structure. Topics connected directly in adjacency list using memory mapped files realize to search at high speed. In addition, we propose a method to speed up the search of the topic based on its nature.

Original language	English
Title of host publication	Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	158-163
Number of pages	6
Volume	2018-February
ISBN (Electronic)	9781538629413
DOIs	https://doi.org/10.1109/ISCSIC.2017.44
Publication status	Published - 2018 Feb 16
Event	1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017 - Budapest, Hungary Duration: 2017 Oct 20 → 2017 Oct 22

Other

Other	1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017
Country/Territory	Hungary
City	Budapest
Period	17/10/20 → 17/10/22

Keywords

data mining
database management system
indexing;
topic maps

ASJC Scopus subject areas

Computer Science Applications
Artificial Intelligence

Access to Document

10.1109/ISCSIC.2017.44

Cite this

Yuta, S., Kimura, M., & Yuki, T. (2018). A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics. In Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017 (Vol. 2018-February, pp. 158-163). [8294178] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCSIC.2017.44

A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics. / Yuta, Shibata; Kimura, Masaomi; Yuki, Toba.
Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017. Vol. 2018-February Institute of Electrical and Electronics Engineers Inc., 2018. p. 158-163 8294178.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yuta, S, Kimura, M & Yuki, T 2018, A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics. in Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017. vol. 2018-February, 8294178, Institute of Electrical and Electronics Engineers Inc., pp. 158-163, 1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017, Budapest, Hungary, 17/10/20. https://doi.org/10.1109/ISCSIC.2017.44

@inproceedings{74f0252b34a24535aa09a10c46645775,

title = "A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics",

abstract = "A topic map has composed a topic expressing concepts, an association between the concepts and a role of association. A topic map database is currently existed to be utilized to a system. The existing Topic map database (TMDB) uses a system such as relational database and object oriented database, and it was necessary to convert from the structure of each system to a topic map structure. Therefore, we propose a native TMDB management system that can store and manipulate data without changing the data structure. Topics connected directly in adjacency list using memory mapped files realize to search at high speed. In addition, we propose a method to speed up the search of the topic based on its nature.",

keywords = "data mining, database management system, indexing;, topic maps",

author = "Shibata Yuta and Masaomi Kimura and Toba Yuki",

year = "2018",

month = feb,

day = "16",

doi = "10.1109/ISCSIC.2017.44",

language = "English",

volume = "2018-February",

pages = "158--163",

booktitle = "Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017 ; Conference date: 20-10-2017 Through 22-10-2017",

}

TY - GEN

T1 - A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics

AU - Yuta, Shibata

AU - Kimura, Masaomi

AU - Yuki, Toba

PY - 2018/2/16

Y1 - 2018/2/16

N2 - A topic map has composed a topic expressing concepts, an association between the concepts and a role of association. A topic map database is currently existed to be utilized to a system. The existing Topic map database (TMDB) uses a system such as relational database and object oriented database, and it was necessary to convert from the structure of each system to a topic map structure. Therefore, we propose a native TMDB management system that can store and manipulate data without changing the data structure. Topics connected directly in adjacency list using memory mapped files realize to search at high speed. In addition, we propose a method to speed up the search of the topic based on its nature.

AB - A topic map has composed a topic expressing concepts, an association between the concepts and a role of association. A topic map database is currently existed to be utilized to a system. The existing Topic map database (TMDB) uses a system such as relational database and object oriented database, and it was necessary to convert from the structure of each system to a topic map structure. Therefore, we propose a native TMDB management system that can store and manipulate data without changing the data structure. Topics connected directly in adjacency list using memory mapped files realize to search at high speed. In addition, we propose a method to speed up the search of the topic based on its nature.

KW - data mining

KW - database management system

KW - indexing;

KW - topic maps

UR - http://www.scopus.com/inward/record.url?scp=85052404732&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052404732&partnerID=8YFLogxK

U2 - 10.1109/ISCSIC.2017.44

DO - 10.1109/ISCSIC.2017.44

M3 - Conference contribution

AN - SCOPUS:85052404732

VL - 2018-February

SP - 158

EP - 163

BT - Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017

Y2 - 20 October 2017 through 22 October 2017

ER -

A Native Topic Map Database Management System and Its N-gram Index for Efficient Search of Topics

Abstract

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this