Àüü
ÀüÀÚ/Àü±â
Åë½Å
ÄÄÇ»ÅÍ
·Î±×ÀÎ
ȸ¿ø°¡ÀÔ
About Us
ÀÌ¿ë¾È³»
¿¬±¸¹®Çå
±¹³» ³í¹®Áö
¿µ¹® ³í¹®Áö
±¹³» ÇÐȸÁö
Çмú´ëȸ ÇÁ·Î½Ãµù
±¹³» ÇÐÀ§ ³í¹®
³í¹®Á¤º¸
¹é¼
±³À°Á¤º¸
¿¬±¸ ù°ÉÀ½
ÇаúÁ¤º¸
°ÀÇÁ¤º¸
µ¿¿µ»óÁ¤º¸
E-Learning
¿Â¶óÀÎ Àú³Î
½ÉÈÁ¤º¸
¿¬±¸ ¹× ±â¼úµ¿Çâ
Áֿ俬±¸ÅäÇÈ
ÁÖ¿ä°úÁ¦ ¹× ±â°ü
Çؿܱâ°ü °ü·ÃÀÚ·á
¹ÙÀÌ¿À Á¤º¸±â¼ú
ÁÖ¿ä Archive Site
Æ÷Ä¿½ºiN
¿¬±¸ÀÚ Á¤º¸
¶óÀÌ¡½ºÅ¸
ÆÄ¿öiNÅͺä
¼¼ÁßÇÑ
¿¬±¸ÀÚ·á
¹®ÀÚ DB
¿ë¾î»çÀü
¾Ë¸²¸¶´ç
ºÎ½Ç ÇмúÈ°µ¿ ¿¹¹æ
³í¹®¸ðÁý
´ëȸ¾È³»
What's New
¿¬±¸ºñÁ¤º¸
±¸ÀÎÁ¤º¸
°øÁö»çÇ×
CSERIC ±¤Àå
Post-Conference
¿¬±¸ÀÚ Ä«Æä
ÀÚÀ¯°Ô½ÃÆÇ
Q&A
´Ý±â
»çÀÌÆ®¸Ê
¿¬±¸¹®Çå
±¹³» ³í¹®Áö
¿µ¹® ³í¹®Áö
±¹³» ÇÐȸÁö
Çмú´ëȸ ÇÁ·Î½Ãµù
±¹³» ÇÐÀ§ ³í¹®
³í¹®Á¤º¸
¹é¼
±³À°Á¤º¸
¿¬±¸ ù°ÉÀ½
ÇаúÁ¤º¸
°ÀÇÁ¤º¸
µ¿¿µ»óÁ¤º¸
E-Learning
¿Â¶óÀÎ Àú³Î
½ÉÈÁ¤º¸
¿¬±¸ ¹× ±â¼úµ¿Çâ
Áֿ俬±¸ÅäÇÈ
ÁÖ¿ä°úÁ¦ ¹× ±â°ü
Çؿܱâ°ü °ü·ÃÀÚ·á
¹ÙÀÌ¿À Á¤º¸±â¼ú
ÁÖ¿ä Archive Site
ÄÄÇ»ÅÍiN
¿¬±¸ÀÚ Á¤º¸
¿¬±¸ÀÚ·á
¹®ÀÚ DB
Ȧ·Î±×·¥ DB
¿ë¾î»çÀü
¾Ë¸²¸¶´ç
ºÎ½Ç ÇмúÈ°µ¿ ¿¹¹æ
³í¹®¸ðÁý
´ëȸ¾È³»
What's New
¿¬±¸ºñ Á¤º¸
±¸ÀÎÁ¤º¸
°øÁö»çÇ×
IT Daily
CSERIC ±¤Àå
Post-Conference
¿¬±¸ÀÚ Ä«Æä
ÀÚÀ¯°Ô½ÃÆÇ
Q&A
¼ºñ½º ¹Ù·Î°¡±â
¼³¹®Á¶»ç
¿¬±¸À±¸®
°ü·Ã±â°ü
Please wait....
¿¬±¸¹®Çå
±¹³» ³í¹®Áö
¿µ¹® ³í¹®Áö
±¹³» ÇÐȸÁö
Çмú´ëȸ ÇÁ·Î½Ãµù
±¹³» ÇÐÀ§ ³í¹®
³í¹®Á¤º¸
¹é¼
±¹³» ³í¹®Áö
Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö >
Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö
>
Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)
Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)
Current Result Document :
1
/ 31
´ÙÀ½°Ç
ÇѱÛÁ¦¸ñ(Korean Title)
äÆà ´ëÈÀÇ ±¸¹®Àû Ư¼ºÀ» ÀÌ¿ëÇÑ Å©·Î½º-ÅؽºÆà ¹æÁö ½Ã½ºÅÛ
¿µ¹®Á¦¸ñ(English Title)
A Cross-Texting Prevention System Using Syntactic Characteristics of Chat Messages
ÀúÀÚ(Author)
ÀÌ´Ù¿µ
Á¶È¯±Ô
Da-Young Lee
Hwan-Gue Cho
¿ø¹®¼ö·Ïó(Citation)
VOL 48 NO. 06 PP. 0639 ~ 0648 (2021. 06)
Çѱ۳»¿ë
(Korean Abstract)
Å©·Î½º-ÅؽºÆÃ(cross-texting)Àº ½Ç¼ö·Î ÀǵµÇÏÁö ¾ÊÀº »ó´ë¹æ¿¡°Ô ¸Þ½ÃÁö¸¦ À߸ø Àü¼ÛÇÏ´Â °ÍÀ» ¸»ÇÑ´Ù. ´Ù¼öÀÇ »ó´ë¹æ°ú µ¿½Ã¿¡ ´ëÈÇÒ ¶§ ºó¹øÇÏ°Ô ¹ß»ýÇÏ´Â ¹®Á¦·Î, ¸Þ½ÅÀú¿¡¼´Â ÁÖ·Î ¹ß¼Û Ãë¼Ò¶ó´Â ±â´ÉÀ» Á¦°øÇÏÁö¸¸ ÀÌ´Â »çÈÄ ÇØ°áÃ¥¿¡ ÇØ´çÇϸç, »ç¿ëÀÚ°¡ »çÀü¿¡ ½Ç¼ö¸¦ ¹æÁöÇϱâ´Â ¾î·Æ´Ù. º» ³í¹®¿¡¼´Â äÆà ¹®ÀåÀÇ Çü½ÄÀû Ư¡À» ºÐ¼®ÇÏ¿© Å©·Î½º-ÅؽºÆÃÀ» ŽÁöÇÏ´Â ¸ðµ¨À» Á¦¾ÈÇß´Ù. äÆà ¹®Àå¿¡¼ ³ôÀÓ¹ý, Ç¥ÃþÀû ¿Ï¼ºµµ ÀÚÁúÀ» ÃßÃâÇØ Æ¯Á¤ »ç¿ëÀÚÀÇ ÀÌÀü ´ëȸ¦ ¸ðµ¨¸µÇÏ°í, ÇöÀç ÁÖ¾îÁø ¹®ÀåÀÌ »ç¿ëÀÚ ´ëÈ ¸ðµ¨¿¡ ºÎÇÕÇÏ´ÂÁö ¿©ºÎ·Î Å©·Î½º-ÅؽºÆÃÀ» ŽÁöÇÑ´Ù. ÀÌ¿Í °°Àº ¹æ¹ýÀº »ç¿ëÀÚÀÇ Ã¤Æà ŵµÀÇ ÀÏ°ü¼ºÀ» ¸ðµ¨¸µÇÔÀ¸·Î½á ÀÇ¹Ì ºÐ¼®À» ÇÏÁö ¾Ê°í Çü½ÄÀû ÀÚÁú¸¸À¸·Î ¹®Á¦¸¦ ÇØ°áÇѵ¥ ÀÇÀÇ°¡ ÀÖ´Ù. º» ³í¹®¿¡¼ ±¸ÇöÇÑ ½Ã½ºÅÛÀ¸·Î ½ÇÁ¦ ¸Þ½ÅÀú ´ëÈ ¸»¹¶Ä¡¸¦ ÀÌ¿ëÇØ ÀÚµ¿À¸·Î »ý¼ºÇÑ µ¥ÀÌÅÍ¿¡¼ 85.5% Á¤È®µµ·Î Å©·Î½º-ÅؽºÆÃÀ» ŽÁöÇÒ ¼ö ÀÖÀ½À» È®ÀÎÇÏ¿´´Ù.
¿µ¹®³»¿ë
(English Abstract)
Cross-texting refers to accidentally sending a message to an unintended person. It occurs frequently when users chat with multiple counterparts at the same time. Messengers mainly provide a function of canceling sending, but it is only post solution, and users find it difficult to prevent mistakes in advance. In this paper, we proposed a cross-texting detection model by analyzing the syntactic characteristics of chat sentences. It modelizes the previous chat messages of a specific user by extracting the honorifics and completeness features from chat messages, and detects the cross-texting cases by determining whether the target sentences are in accordance with the user chat message model. This approach is significant as it solves the cross-texting detection problem only with syntactic characteristics without semantic analysis by modeling the consistency of the user's chat attitude. The proposed model detect cross-texting cases with an accuracy of 85.5% from automatically generated data using a real messenger dialogue corpus.
Å°¿öµå(Keyword)
äÆà ¸Þ½ÃÁö
Å©·Î½º-ÅؽºÆÃ
³ôÀÓ¸» Ç¥Çö
¹®Àå ¿Ï¼ºµµ
¹®Àå º¤ÅÍ
chat message
cross-texting
honorifics
sentence completeness
sentence vector
ÆÄÀÏ÷ºÎ
PDF ´Ù¿î·Îµå
¸ñ·Ï
Copyright(c)
Computer Science Engineering Research Information Center
. All rights reserved.