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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.
