Korean Compound Noun Term Analysis Based on a Chart Parsing Technique

Min, Kyongho; Wilson, William H.; Moon, Yoo-Jin

doi:10.1007/978-3-540-24581-0_16

Cited by 1 publication

(1 citation statement)

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“…In particular, decomposition of compound nouns is nontrivial in Korean (Kang, 1993(Kang, , 1998Choi, 1996;Jang and Myaeng, 1996;Park et al, 1996;Yun et al, 1997;Lee et al, 1999;Shim, 1999;Yoon, 2001;Min et al, 2003;Park et al, 2004), since there may be unknown component words and segmentation ambiguity in compound nouns. Today, due to globalization, unknown words are growing faster than ever before, especially in nominals.…”

Section: Introductionmentioning

confidence: 96%

Collection-based compound noun segmentation for Korean information retrieval

Kang

Lee

2006

Inf Retrieval

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Compound noun segmentation is a key first step in language processing for Korean. Thus far, most approaches require some form of human supervision, such as pre-existing dictionaries, segmented compound nouns, or heuristic rules. As a result, they suffer from the unknown word problem, which can be overcome by unsupervised approaches. However, previous unsupervised methods normally do not consider all possible segmentation candidates, and/or rely on character-based segmentation clues such as bi-grams or all-length n-grams. So, they are prone to falling into a local solution. To overcome the problem, this paper proposes an unsupervised segmentation algorithm that searches the most likely segmentation result from all possible segmentation candidates using a word-based segmentation context. As wordbased segmentation clues, a dictionary is automatically generated from a corpus. Experiments using three test collections show that our segmentation algorithm is successfully applied to Korean information retrieval, improving a dictionary-based longest-matching algorithm.

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