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¢º ÁÖÁ¦: ¿¬±¸¹æ¹ý·Ð ¿öÅ©¼ó : Topic Modeling (ÅäÇȸðÇü)
¢º °»ç: ±è¼ºÇö ±³¼ö (¹Ì±¹ ǽ·¯´ëÇб³ ½É¸®ÇÐ ´ëÇпø Á¶±³¼ö)
¢º ÀϽÃ: 2015³â 7¿ù 10ÀÏ(±Ý)~11ÀÏ(Åä), ¿ÀÀü 9½Ã 30ºÐ ~ ¿ÀÈÄ 5½Ã (ÃÑ 12½Ã°£)
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Âü°¡ºñ ÀÔ±Ý(15¸¸¿ø, ½ÅÇÑÀºÇà 110-353-319700 ¿¹±ÝÁÖ: ¾çÇÞ»ì)
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* 7¿ù 1ÀÏ(¼ö)±îÁö Ãë¼Ò½Ã Âü°¡ºñ Àü¾×ȯºÒ, 7¿ù 6ÀÏ(¿ù)±îÁö Ãë¼Ò½Ã 50%ȯºÒ,
7¿ù 7ÀÏ(È)ÀÌÈÄ Ãë¼Ò´Â Çà»ç¿î¿µ»ó ȯºÒÇÏÁö ¾Ê½À´Ï´Ù.
1. Topic modeling (ÅäÇÈ ¸ðÇü) ¼Ò°³
Topic ModelingÀº ÅؽºÆ® ÀÚ·á(¿¹: »ó´ã Ãà¾î·Ï, ¿Â¶óÀÎ »ó´ã °Ô½Ã¹° µî)¸¦ ¾çÀûÀ¸·Î ºÐ¼®ÇÏ´Â Åë°èÀû ¹æ¹ýÀÔ´Ï´Ù. ¿äÀκм®¿¡¼ ¹®Ç×µé °£ÀÇ »ó°üÀ» ÀÌ¿ëÇØ ¿äÀÎÀ» ã´Â °Íó·³ ÅؽºÆ® ÀÚ·á¿¡¼ ´Ü¾îµé°£ÀÇ ¿¬°ü °ü°è¸¦ ÀÌ¿ëÇØ ÀáÀçµÈ topicÀ» ÃßÃâÇÏ´Â ±â¹ýÀÔ´Ï´Ù. ºÐ¼® ´ë»óÀÌ ¹®Ç×ÀÌ ¾Æ´Ï¶ó ÅؽºÆ® ÀÚ·á¶ó´Â Á¡¿¡¼ Â÷ÀÌ°¡ ÀÖ½À´Ï´Ù.
Topic modelingÀº ºòµ¥ÀÌŸ ºÐ¼®(big data analysis), ÀÚ¿¬¾î ó¸®(natural language processing), ±â°è ÇнÀ(machine learning) µî°ú ¹ÐÁ¢ÇÑ °ü·ÃÀÌ ÀÖ½À´Ï´Ù.
2. °»ç ¾à·Â
±è¼ºÇö ±³¼ö´Ô (¹Ì±¹ ǽ·¯´ëÇб³ ½É¸®ÇÐ ´ëÇпø Á¶±³¼ö)
- ¼¿ï´ëÇб³ ±³À°Çаú Çлç, ¼®»ç
- Florida State University Counseling Center ¼ö·Ã
- University of Texas at Austin ¹Ú»ç
3. ¼¼ºÎ ÀÏÁ¤
7¿ù 10ÀÏ (±Ý¿äÀÏ) : 1ÀÏÂ÷
9:00~9:30 |
µî·Ï |
9:30~9:40 |
Àλ縻: ±èµ¿¹Î(Çѱ¹»ó´ãÇÐȸ ¼¿ï°æ±âÀÎõ»ó´ãÇÐȸÀå) |
9:40~12:40 |
1. Topic modeling: ¼Ò°³ (¹ß´Þ»ç, °ü·Ã ¸ðÇü, °³³ä µî)
2. Topic modeling: È°¿ë (»ó´ã/ÀÓ»ó ½É¸®, ½É¸® °Ë»ç µî)
3. R ´Ù¿î·Îµå/¼³Ä¡ |
12:40~14:00 |
Á¡½É½Ä»ç |
14:00~17:00 |
1. R ¼Ò°³: ÀڷᱸÁ¶ &¸í·É¾î µî
2. ÅؽºÆ® µ¥ÀÌÅÍÀÇ ÀÔ·Â &Àüó¸® (pre-processing) |
7¿ù 11ÀÏ (Åä¿äÀÏ) : 2ÀÏÂ÷
9:00~9:30 |
µî·Ï |
9:30~12:30 |
1. Text analysis: Descriptives, »ó°ü, ±ºÁýºÐ¼® µî
2. Latent Dirichlet Allocation (LDA) ¼Ò°³ ¹× ºÐ¼®, ¿¹½Ã |
12:30~14:00 |
Á¡½É½Ä»ç |
14:00~17:00 |
1. Correlated topic model: »ó°ü ÅäÇÈ ¸ðÇü
2. Dynamic topic model: Á¾´Ü ÅäÇÈ ¸ðÇü
3. Advanced topics: Çѱ¹ µ¥ÀÌÅ͸¦ È°¿ëÇÑ ¿¹½Ã | |