Rules for ontology population from text of malaysia medicinal herbs domain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The primary goal of ontology development is to share and reuse domain knowledge among people or machines. This study focuses on the approach of extracting semantic relationships from unstructured textual documents related to medicinal herb from websites and proposes a lexical pattern technique to acquire semantic relationships such as synonym, hyponym, and part-of relationships. The results show of nine object properties (or relations) and 105 lexico-syntactic patterns have been identified manually, including one from the Hearst hyponym rules. The lexical patterns have linked 7252 terms that have the potential as ontological terms. Based on this study, it is believed that determining the lexical pattern at an early stage is helpful in selecting relevant term from a wide collection of terms in the corpus. However, the relations and lexico-syntactic patterns or rules have to be verified by domain expert before employing the rules to the wider collection in an attempt to find more possible rules.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages386-394
Number of pages9
Volume6401 LNAI
DOIs
Publication statusPublished - 2010
Event5th International Conference on Rough Set and Knowledge Technology, RSKT 2010 - Beijing
Duration: 15 Oct 201017 Oct 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6401 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Conference on Rough Set and Knowledge Technology, RSKT 2010
CityBeijing
Period15/10/1017/10/10

Fingerprint

Malaysia
Syntactics
Ontology
Semantics
Websites
Term
Domain Knowledge
Reuse
Text
Relationships

Keywords

  • knowledge engineering
  • Knowledge management and extraction
  • medicinal herb
  • Natural Language Processing
  • semantic web

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ibrahim, Z., Mohd Noah, S. A., & Mat Noor, M. (2010). Rules for ontology population from text of malaysia medicinal herbs domain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6401 LNAI, pp. 386-394). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6401 LNAI). https://doi.org/10.1007/978-3-642-16248-0_55

Rules for ontology population from text of malaysia medicinal herbs domain. / Ibrahim, Zaharudin; Mohd Noah, Shahrul Azman; Mat Noor, Mahanem.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI 2010. p. 386-394 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6401 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ibrahim, Z, Mohd Noah, SA & Mat Noor, M 2010, Rules for ontology population from text of malaysia medicinal herbs domain. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 6401 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6401 LNAI, pp. 386-394, 5th International Conference on Rough Set and Knowledge Technology, RSKT 2010, Beijing, 15/10/10. https://doi.org/10.1007/978-3-642-16248-0_55
Ibrahim Z, Mohd Noah SA, Mat Noor M. Rules for ontology population from text of malaysia medicinal herbs domain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI. 2010. p. 386-394. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-16248-0_55
Ibrahim, Zaharudin ; Mohd Noah, Shahrul Azman ; Mat Noor, Mahanem. / Rules for ontology population from text of malaysia medicinal herbs domain. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6401 LNAI 2010. pp. 386-394 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{49bdea699dd14c029700558ae98e2830,
title = "Rules for ontology population from text of malaysia medicinal herbs domain",
abstract = "The primary goal of ontology development is to share and reuse domain knowledge among people or machines. This study focuses on the approach of extracting semantic relationships from unstructured textual documents related to medicinal herb from websites and proposes a lexical pattern technique to acquire semantic relationships such as synonym, hyponym, and part-of relationships. The results show of nine object properties (or relations) and 105 lexico-syntactic patterns have been identified manually, including one from the Hearst hyponym rules. The lexical patterns have linked 7252 terms that have the potential as ontological terms. Based on this study, it is believed that determining the lexical pattern at an early stage is helpful in selecting relevant term from a wide collection of terms in the corpus. However, the relations and lexico-syntactic patterns or rules have to be verified by domain expert before employing the rules to the wider collection in an attempt to find more possible rules.",
keywords = "knowledge engineering, Knowledge management and extraction, medicinal herb, Natural Language Processing, semantic web",
author = "Zaharudin Ibrahim and {Mohd Noah}, {Shahrul Azman} and {Mat Noor}, Mahanem",
year = "2010",
doi = "10.1007/978-3-642-16248-0_55",
language = "English",
isbn = "3642162479",
volume = "6401 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "386--394",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Rules for ontology population from text of malaysia medicinal herbs domain

AU - Ibrahim, Zaharudin

AU - Mohd Noah, Shahrul Azman

AU - Mat Noor, Mahanem

PY - 2010

Y1 - 2010

N2 - The primary goal of ontology development is to share and reuse domain knowledge among people or machines. This study focuses on the approach of extracting semantic relationships from unstructured textual documents related to medicinal herb from websites and proposes a lexical pattern technique to acquire semantic relationships such as synonym, hyponym, and part-of relationships. The results show of nine object properties (or relations) and 105 lexico-syntactic patterns have been identified manually, including one from the Hearst hyponym rules. The lexical patterns have linked 7252 terms that have the potential as ontological terms. Based on this study, it is believed that determining the lexical pattern at an early stage is helpful in selecting relevant term from a wide collection of terms in the corpus. However, the relations and lexico-syntactic patterns or rules have to be verified by domain expert before employing the rules to the wider collection in an attempt to find more possible rules.

AB - The primary goal of ontology development is to share and reuse domain knowledge among people or machines. This study focuses on the approach of extracting semantic relationships from unstructured textual documents related to medicinal herb from websites and proposes a lexical pattern technique to acquire semantic relationships such as synonym, hyponym, and part-of relationships. The results show of nine object properties (or relations) and 105 lexico-syntactic patterns have been identified manually, including one from the Hearst hyponym rules. The lexical patterns have linked 7252 terms that have the potential as ontological terms. Based on this study, it is believed that determining the lexical pattern at an early stage is helpful in selecting relevant term from a wide collection of terms in the corpus. However, the relations and lexico-syntactic patterns or rules have to be verified by domain expert before employing the rules to the wider collection in an attempt to find more possible rules.

KW - knowledge engineering

KW - Knowledge management and extraction

KW - medicinal herb

KW - Natural Language Processing

KW - semantic web

UR - http://www.scopus.com/inward/record.url?scp=78349268306&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78349268306&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-16248-0_55

DO - 10.1007/978-3-642-16248-0_55

M3 - Conference contribution

SN - 3642162479

SN - 9783642162473

VL - 6401 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 386

EP - 394

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -