Paper: A Syllable Based Word Recognition Model For Korean Noun Extraction

ACL ID P03-1060
Title A Syllable Based Word Recognition Model For Korean Noun Extraction
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2003
Authors

Noun extraction is very important for many NLP applications such as informa- tion retrieval, automatic text classification, and information extraction. Most of the previous Korean noun extraction systems use a morphological analyzer or a Part- of-Speech (POS) tagger. Therefore, they require much of the linguistic knowledge such as morpheme dictionaries and rules (e.g. morphosyntactic rules and morpho- logical rules). This paper proposes a new noun extrac- tion method that uses the syllable based word recognition model. It finds the most probable syllable-tag sequence of the input sentence by using automatically acquired statistical information from the POS tagged corpus and extracts nouns by detecting word boundaries. Furthermore, it does not require any labor for construct- ing and mainta...