{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T14:46:37Z","timestamp":1704206797555},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2001,7,25]],"date-time":"2001-07-25T00:00:00Z","timestamp":996019200000},"content-version":"unspecified","delay-in-days":54,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nat. Lang. Eng."],"published-print":{"date-parts":[[2001,6]]},"abstract":"<jats:p>Compound noun segmentation is one of the crucial problems in Korean language processing \nbecause a series of nouns in Korean may appear without space in real text, which makes it \ndifficult to identify its morphological constituents. This paper presents an effective method \nof Korean compound noun segmentation based on lexical data extracted from a corpus. \nThe segmentation consists of two tasks: First, it uses a Hand-Build Segmentation Dictionary \n(HBSD) to segment compound nouns which frequently occur or need an exceptional process. \nSecond, a segmentation algorithm using data from a corpus is proposed, where simple nouns \nand their frequencies are stored in a Simple Noun Dictionary (SND) for segmentation. \nThe analysis is executed based on modified tabular parsing using min-max operation. Our \nexperiments have shown a very effective accuracy rate of about 97.29%, which turns out to \nbe very effective.<\/jats:p>","DOI":"10.1017\/s1351324901002637","type":"journal-article","created":{"date-parts":[[2002,7,27]],"date-time":"2002-07-27T13:16:52Z","timestamp":1027775812000},"page":"167-185","source":"Crossref","is-referenced-by-count":3,"title":["Compound noun segmentation based on lexical data extracted from corpus"],"prefix":"10.1017","volume":"7","author":[{"given":"JUNTAE","family":"YOON","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2001,7,25]]},"container-title":["Natural Language Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1351324901002637","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,3,29]],"date-time":"2019-03-29T19:02:45Z","timestamp":1553886165000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1351324901002637\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,6]]},"references-count":0,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2001,6]]}},"alternative-id":["S1351324901002637"],"URL":"https:\/\/doi.org\/10.1017\/s1351324901002637","relation":{},"ISSN":["1351-3249","1469-8110"],"issn-type":[{"value":"1351-3249","type":"print"},{"value":"1469-8110","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,6]]}}}