Knowledge acquisition from textual documents for the construction of medicinal herbs domain ontology

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this study a semi automatic acquisition of domain relevant terms from digital documents in e-newspaper related to Malaysian medicinal herbs is presented. This study proposes (1) TFIDF-based term classification method for acquiring single word terms, (2) recognition of multi-word using TerMine software to acquire multiword terms and (3) Hearst's methodology of acquiring semantic relationships of hyponym. The results show the benefits of using these methods in selecting relevant terms from domain specific corpus. From this study it is believed that the combination of these three methods might be helpful to select relevant terms as well as minimize the effort to discard irrelevant terms manually-from wide collection of terms from the corpus.

Original languageEnglish
Pages (from-to)794-798
Number of pages5
JournalJournal of Applied Sciences
Volume9
Issue number4
Publication statusPublished - 2009

Fingerprint

Knowledge acquisition
Ontology
Semantics

Keywords

  • Biomedical
  • Knowledge engineering
  • Knowledge management and extraction
  • Malaysian medicinal herb
  • Natural language processing
  • Semantic web

ASJC Scopus subject areas

  • General

Cite this

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abstract = "In this study a semi automatic acquisition of domain relevant terms from digital documents in e-newspaper related to Malaysian medicinal herbs is presented. This study proposes (1) TFIDF-based term classification method for acquiring single word terms, (2) recognition of multi-word using TerMine software to acquire multiword terms and (3) Hearst's methodology of acquiring semantic relationships of hyponym. The results show the benefits of using these methods in selecting relevant terms from domain specific corpus. From this study it is believed that the combination of these three methods might be helpful to select relevant terms as well as minimize the effort to discard irrelevant terms manually-from wide collection of terms from the corpus.",
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AB - In this study a semi automatic acquisition of domain relevant terms from digital documents in e-newspaper related to Malaysian medicinal herbs is presented. This study proposes (1) TFIDF-based term classification method for acquiring single word terms, (2) recognition of multi-word using TerMine software to acquire multiword terms and (3) Hearst's methodology of acquiring semantic relationships of hyponym. The results show the benefits of using these methods in selecting relevant terms from domain specific corpus. From this study it is believed that the combination of these three methods might be helpful to select relevant terms as well as minimize the effort to discard irrelevant terms manually-from wide collection of terms from the corpus.

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KW - Natural language processing

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