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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ ³í¹®Áö

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Current Result Document : 4 / 5 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) È¿À²ÀûÀÎ ¹®¼­ ºÐ·ù¸¦ À§ÇÑ È¥ÇÕ Æ¯Â¡ ÁýÇÕ°ú ÇÏÀ̺긮µå Ư¡ ¼±Åà ±â¹ý
¿µ¹®Á¦¸ñ(English Title) Combined Feature Set and Hybrid Feature Selection Method for Effective Document Classification
ÀúÀÚ(Author) ÀÎÁÖÈ£   ±èÁ¤È£   ä¼öȯ   Joo-ho In   Jung-ho Kim   Soo-hoan Chae  
¿ø¹®¼ö·Ïó(Citation) VOL 14 NO. 05 PP. 0049 ~ 0057 (2013. 10)
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(Korean Abstract)
º» ¿¬±¸¿¡¼­´Â È¿À²ÀûÀÎ ¿Â ¶óÀÎ ¹®¼­ ÀÚµ¿ ºÐ·ù¸¦ À§ÇØ ¸Å¿ì Áß¿äÇÑ ºÐ·ù ÀÛ¾÷ÀÇ Àüó¸® ´Ü°èÀΠƯ¡¼±ÅÃÀ» À§ÇÑ »õ·Î¿î ¹æ¹ýÀÌ Á¦¾ÈµÈ´Ù. ´ëºÎºÐÀÇ ±âÁ¸ Ư¡¼±Åà ¹æ¹ý ¿¬±¸¿¡¼­´Â Ư¡ ÁýÇÕÀÇ ¸ðÁý´ÜÀÌ ´ÜÀÏ ¸ðÁý´ÜÀ¸·Î½á ÇÑ ¸ðÁý´ÜÀÌ °¡Áö´Â Á¤º¸¸¸À¸·Î ºÐ·ù¿¡ ÀûÇÕÇÑ Æ¯Â¡µéÀ» ¼±ÅÃÇÏ¿© Ư¡ ÁýÇÕÀ» ±¸¼ºÇÏ¿´´Ù. º» ¿¬±¸¿¡¼­´Â ´ÜÀÏ ¸ðÁý´Ü¿¡ ÇÑÇÏ¿© ¼öÇàµÇ´Â Ư¡¼±Åà »Ó ¸¸ ¾Æ´Ï¶ó, ´ÙÁß ¸ðÁý´ÜÀ» °¡Áö´Â È¥ÇÕ Æ¯Â¡ ÁýÇÕ¿¡ ´ëÇؼ­ Ư¡¼±ÅÃÀ» ÇÔÀ¸·Î½á ´Ù¾çÇÑ Á¤º¸¸¦ ¹ÙÅÁÀ¸·Î ÇÑ Æ¯Â¡ ÁýÇÕÀ» ±¸¼ºÇÏ¿´´Ù. È¥ÇÕ Æ¯Â¡ ÁýÇÕÀº µÎ Á¾·ùÀÇ Æ¯Â¡ ÁýÇÕÀ¸·Î ±¸¼ºµÈ´Ù. Áï °¢°¢ ¹®¼­·ÎºÎÅÍ ÃßÃâÇÑ ´Ü¾î·Î ±¸¼ºµÈ ¿øº» Ư¡ ÁýÇÕ°ú ¿øº» Ư¡ ÁýÇÕÀ¸·ÎºÎÅÍ LSA¸¦ ÀÌ¿ëÇÏ¿© »õ·Î »ý¼ºÇÑ º¯Çü Ư¡ ÁýÇÕÀÌ´Ù. È¥ÇÕ Æ¯Â¡ ÁýÇÕÀ¸·ÎºÎÅÍ ÇÊÅÍ ¹æ¹ý°ú ·¡ÆÛ ¹æ¹ýÀ» ÀÌ¿ëÇÑ ÇÏÀ̺긮µå ¹æ½ÄÀÇ Æ¯Â¡ ¼±ÅÃÀ» ÅëÇØ ÃÖÀûÀÇ Æ¯Â¡ ÁýÇÕÀ» ã°í, À̸¦ ÀÌ¿ëÇÏ¿© ¹®¼­ ºÐ·ù ½ÇÇèÀ» ¼öÇàÇÏ¿´´Ù. ´Ù¾çÇÑ ¸ðÁý´ÜÀÇ Æ¯Â¡µéÀÇ Á¤º¸¸¦ ¸ðµÎ °í·ÁÇÔÀ¸·Î½á º¸´Ù Çâ»óµÈ ºÐ·ù ¼º´ÉÀ» º¸ÀÏ °ÍÀ̶ó°í ±â´ëÇÏ¿´°í, ÀÎÅÍ³Ý ´º½º ±â»ç¸¦ ´ë»óÀ¸·Î ºÐ·ù ½ÇÇèÇÑ °á°ú 90% ÀÌ»óÀÇ Çâ»óµÈ ºÐ·ù¼º´ÉÀ» È®ÀÎÇÏ¿´´Ù. ƯÈ÷, ÀçÇöÀ²°ú Á¤¹Ðµµ ¸ðµÎ 90%ÀÌ»óÀÇ ¼º´ÉÀ» º¸¿´À¸¸ç, µÑ »çÀÌÀÇ ÆíÂ÷°¡ ³·Àº °ÍÀ» È®ÀÎÇÏ¿´´Ù.
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(English Abstract)
A novel approach for the feature selection is proposed, which is the important preprocessing task of on-line document classification. In previous researches, the features based on information from their single population for feature selection task have been selected. In this paper, a mixed feature set is constructed by selecting features from multi-population as well as single population based on various information. The mixed feature set consists of two feature sets: the original feature set that is made up of words on documents and the transformed feature set that is made up of features generated by LSA. The hybrid feature selection method using both filter and wrapper method is used to obtain optimal features set from the mixed feature set. We performed classification experiments using the obtained optimal feature sets. As a result of the experiments, our expectation that our approach makes better performance of classification is verified, which is over 90% accuracy. In particular, it is confirmed that our approach has over 90% recall and precisionthat have a low deviation between categories.
Å°¿öµå(Keyword) ¹®¼­ ºÐ·ù   Ư¡ ¼±Åà  È¥ÇÕ Æ¯Â¡ ÁýÇÕ   LSA   ÇÏÀ̺긮µå Ư¡ ¼±Åà  document classification   feature selection   mixed feature set   LSA   hybrid feature selection  
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