Summary
|
For Full-Text PDF, please login, if you are a member of IEICE, or go to Pay Per View on menu list, if you are a nonmember of IEICE. |
|
Statistical-Based Approach to Non-segmented Language Processing Virach SORNLERTLAMVANICH Thatsanee CHAROENPORN Shisanu TONGCHIM Canasai KRUENGKRAI Hitoshi ISAHARA Publication IEICE TRANSACTIONS on Information and Systems Vol.E90-D No.10 pp.1565-1573 Publication Date: 2007/10/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e90-d.10.1565 Print ISSN: 0916-8532 Type of Manuscript: Special Section PAPER (Special Section on Knowledge, Information and Creativity Support System) Category: Keyword: non-segmented language, unified language processing, statistical approach, probability, language identification, word extraction, search engine, Full Text: PDF(910.3KB)>>
Summary: Several approaches have been studied to cope with the exceptional features of non-segmented languages. When there is no explicit information about the boundary of a word, segmenting an input text is a formidable task in language processing. Not only the contemporary word list, but also usages of the words have to be maintained to cover the use in the current texts. The accuracy and efficiency in higher processing do heavily rely on this word boundary identification task. In this paper, we introduce some statistical based approaches to tackle the problem due to the ambiguity in word segmentation. The word boundary identification problem is then defined as a part of others for performing the unified language processing in total. To exhibit the ability in conducting the unified language processing, we selectively study the tasks of language identification, word extraction, and dictionary-less search engine. | ||||||||||
| ||||||||||
