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ÇѱÛÁ¦¸ñ(Korean Title) |
ÀÚµ¿ ÃßÃâµÈ Áö½Ä¿¡ ±â¹ÝÇÑ Çѱ¹¾î ÇнÀ Áö¿ø ½Ã½ºÅÛ |
¿µ¹®Á¦¸ñ(English Title) |
Korean Learning Assistant System with Automatically Extracted Knowledge |
ÀúÀÚ(Author) |
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ÀÌÅÂÈÆ
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Gi-Tae Park
Tae-Hoon Lee
So-Hyun Hwang
Byeong Man Kim
Hyun Ah Lee
Yoon Sik Shin
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¿ø¹®¼ö·Ïó(Citation) |
VOL 01 NO. 02 PP. 0091 ~ 0102 (2012. 11) |
Çѱ۳»¿ë (Korean Abstract) |
Á¤º¸Åë½Å±â¼úÀ» È°¿ëÇÑ ÇнÀ½Ã½ºÅÛÀº ²ÙÁØÈ÷ °Á¶µÇ¾î ¿ÔÁö¸¸ Çѱ¹¾î ÇнÀ½Ã½ºÅÛÀÇ ÀÚµ¿È ¼öÁØÀº ³ôÁö ¾Ê´Ù. ½Ç¿ë¼º ÀÖ´Â ÇнÀ½Ã½ºÅÛÀÇ ±¸Ãà¿¡´Â ´ë·®ÀÇ ±â¹ÝÁö½ÄÀÌ ÇÊ¿äÇÏÁö¸¸ ÀÌ·¯ÇÑ Áö½ÄÀ» ±¸ÃàÇϱ⠽±Áö ¾Ê±â ¶§¹®ÀÌ´Ù. º» ³í¹®¿¡¼´Â Çѱ¹¾îÇнÀ½Ã½ºÅÛÀÇ ¿ä¼Ò·Î ¾îÇй®Á¦Ç®ÀÌ, Ç¥ÁعßÀ½ µµ¿ì¹Ì, ±Û¾²±â µµ¿ì¹Ì¸¦ Á¦¾ÈÇÏ°í, ȹµæÀÌ ¿ëÀÌÇÑ ¸»¹¶Ä¡¿Í À¥¹®¼, »çÀüÀ» È°¿ëÇÏ¿© ±¸ÃàµÈ ÇнÀÁö¿ø½Ã½ºÅÛÀ» ¼Ò°³ÇÑ´Ù. ¾îÇй®Á¦Ç®À̸¦ À§ÇÑ ÀÚµ¿¹®Á¦»ý¼º¿¡¼´Â ¸»¹¶Ä¡¿Í »çÀüÀ» ÀÌ¿ëÇÏ¿© ¹®Á¦¿Í º¸±â¹®Ç×À» »ý¼ºÇÏ°í, À¥¹®¼ °Ë»öºóµµ¸¦ È°¿ëÇÏ¿© º¸±âÀûÇÕ¼ºÀ» °ËÁõÇÑ´Ù. Ç¥ÁعßÀ½ º¯È¯À» À§Çؼ ¹ßÀ½Ç¥±â¹ýÀ» ºÐ¼®ÇÏ¿´À¸¸ç, ±Û¾²±â Áö¿øÀ» À§ÇØ ¸»¹¶Ä¡¿¡¼ ÃßÃâÇÑ ±âºÐ¼®µ¥ÀÌÅ͸¦ ÀÌ¿ëÇÑ ½Ç½Ã°£ ¾îÈÖÃßõ°ú ¹®ÀåÃßõÀ» ±¸ÇöÇÏ¿´´Ù. ½ÇÇè¿¡¼´Â Á¦¾ÈÇÏ´Â ¹æ¹ýÀ¸·Î »ý¼ºµÈ ÀÓÀÇÀÇ 400¹®Á¦¿¡ ´ëÇÑ ÆÇÁ¤ °á°ú 89.9%ÀÇ ¹®Á¦ ÀûÇÕ·ü°ú 64.9%ÀÇ º¸±â ÀûÇÕ·üÀ» º¸¿´´Ù. |
¿µ¹®³»¿ë (English Abstract) |
Computer aided language learning has become popular. But the level of automation of constructing a Korean learning assistant system is not so high because a practical language learning system needs large scale knowledge resources, which is very hard to acquire. In this paper, we propose a Korean learning assistant system that utilizes easily obtainable knowledge resources like a corpus, web documents and a lexicon. Our system has three modules - problem solving, pronunciation marker and writing assistant. Automatic problem generator uses a corpus and a lexicon to make problems with one correct answer and three distracters, then verifies their suitability by utilizing frequency information from web documents. We analyze pronunciation rules for a pronunciation marker and recommend appropriate words and sentences in real-time by using data extracted from a corpus. In experiment, we evaluate 400 automatically generated problems, which show 89.9% problem suitability and 64.9% example suitability. |
Å°¿öµå(Keyword) |
Çѱ¹¾îÇнÀ½Ã½ºÅÛ
ÀÚµ¿¹®Á¦»ý¼º
ÀÚµ¿¹ßÀ½Ç¥±â
ÀÚµ¿±Û¾²±âÁö¿ø
Korean Leaning Assistant
Automatic Problem Generation
Automatic Korean Pronunciation Marking
Automatic Writing Assistant
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