\uc800\uc790:<\/strong> \ub2f9\uc2e0\uc758 \uc774\ub984<\/p>\n \uc791\uc131\uc77c:<\/strong> 2023-10-02<\/p>\n<\/header>\n \uc790\uc5f0\uc5b4 \ucc98\ub9ac\ub294 \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ucc98\ub9ac\ud558\ub294 \uae30\uc220 \ubd84\uc57c\ub85c\uc11c, \uc778\uacf5\uc9c0\ub2a5 \ubc0f \uba38\uc2e0\ub7ec\ub2dd\uc758 \ubc1c\uc804\uacfc \ud568\uaed8 \ube60\ub974\uac8c \uc131\uc7a5\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \ub525 \ub7ec\ub2dd \uae30\uc220\uc774 \ub300\ub450\ub418\uba74\uc11c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubd84\uc57c\uc5d0\uc11c\ub3c4 \ub9ce\uc740 \ud601\uc2e0\uc774 \uc774\ub8e8\uc5b4\uc84c\uc2b5\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 BERT(Bidirectional Encoder Representations from Transformers) \ubaa8\ub378\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \ubcf5\ud569 \ud1a0\ud53d \ubaa8\ub378(Combined Topic Models, CTM)\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. CTM\uc740 \ubb38\uc11c \uc548\uc758 \uc5ec\ub7ec \uc8fc\uc81c\ub97c \ubcf4\ub2e4 \ud6a8\uc728\uc801\uc73c\ub85c \ucd94\ucd9c\ud558\uace0, \uc774\ub97c \ud1b5\ud574 \ub370\uc774\ud130\uc758 \uae4a\uc774 \uc788\ub294 \uc774\ud574\ub97c \uac00\ub2a5\ud558\uac8c \ud569\ub2c8\ub2e4.<\/p>\n<\/section>\n \uc790\uc5f0\uc5b4 \ucc98\ub9ac\ub294 \uc5b8\uc5b4\ud559, \ucef4\ud4e8\ud130 \uacfc\ud559 \ubc0f \uc778\uacf5\uc9c0\ub2a5\uc758 \uad50\ucc28\uc810\uc5d0 \uc704\uce58\ud558\uba70, \ud2b9\ud788 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc5d0\uc11c \uc758\ubbf8\ub97c \ucd94\ucd9c\ud574\ub0b4\ub294 \ub370 \uc911\uc810\uc744 \ub461\ub2c8\ub2e4. \uc790\uc5f0\uc5b4 \ucc98\ub9ac\ub97c \uc704\ud574 \uc8fc\ub85c \uc0ac\uc6a9\ud558\ub294 \uae30\ubc95\uc5d0\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \uac83\ub4e4\uc774 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n BERT\ub294 \uad6c\uae00\uc774 \uac1c\ubc1c\ud55c \ub525 \ub7ec\ub2dd \uae30\ubc18\uc758 \uc5b8\uc5b4 \uc774\ud574 \ubaa8\ub378\ub85c, \ubb38\ub9e5\uc744 \uc591\ubc29\ud5a5\uc73c\ub85c \uace0\ub824\ud558\uc5ec \ub2e8\uc5b4\uc758 \uc758\ubbf8\ub97c \uc774\ud574\ud560 \uc218 \uc788\ub294 \ub2a5\ub825\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. BERT\ub294 \ud14d\uc2a4\ud2b8\uc758 \uc21c\uc11c\ub97c \uace0\ub824\ud558\uc9c0 \uc54a\uace0 \uc804\uccb4 \ubb38\uc7a5\uc744 \ud55c \ubc88\uc5d0 \ucc98\ub9ac\ud558\uc5ec, \ubb38\ub9e5\uc758 \ubcc0\ud654\ub97c \ub354\uc6b1 \uc815\ud655\ud558\uac8c \ubc18\uc601\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n BERT\uc758 \uc8fc\uc694 \ud2b9\uc9d5\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n CTM\uc740 \uc804\ud1b5\uc801\uc778 \ud1a0\ud53d \ubaa8\ub378\ub9c1 \uae30\ubc95\uc5d0 BERT\uc758 \uac15\ub825\ud55c \ubb38\ub9e5 \uc774\ud574 \ub2a5\ub825\uc744 \uacb0\ud569\ud55c \ubc29\ubc95\uc785\ub2c8\ub2e4. \uc804\ud1b5\uc801\uc778 \ud1a0\ud53d \ubaa8\ub378\ub9c1 \uae30\ubc95\uc778 LDA(Latent Dirichlet Allocation)\uc640 \uac19\uc740 \ubc29\ubc95\ub4e4\uc740 \ub2e8\uc5b4\uc758 \ub3d9\uc2dc \ubc1c\uc0dd\uc744 \uae30\ubc18\uc73c\ub85c \uc8fc\uc81c\ub97c \ucc3e\ub294 \uae30\ubc95\uc785\ub2c8\ub2e4. \uadf8\ub7ec\ub098, \uc774\ub4e4\uc740 \uc8fc\uc81c\uc758 \ud488\uc9c8\uc5d0 \uc788\uc5b4 \ud55c\uacc4\uac00 \uc788\uc5c8\uc2b5\ub2c8\ub2e4.<\/p>\n CTM\uc740 BERT\ub97c \uc0ac\uc6a9\ud558\ub294 \ubcf5\ud569 \ubaa8\ub378\ub9c1 \uc811\uadfc \ubc29\uc2dd\uc744 \ud1b5\ud574, \ubb38\uc11c\uc758 \uc7a0\uc7ac \uc8fc\uc81c\ub97c \ub354 \uae4a\uc774 \uc788\uac8c \ucd94\ucd9c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:<\/p>\n \uc774\uc81c BERT \uae30\ubc18 CTM\uc744 \uad6c\ud604\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \ud30c\uc774\uc36c\uacfc \uad00\ub828 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \uac04\ub2e8\ud558\uac8c \uad6c\ud604\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798\ub294 \uad6c\ud604 \ub2e8\uacc4\uc785\ub2c8\ub2e4:<\/p>\n \uba3c\uc800 \ubd84\uc11d\ud560 \ubb38\uc11c \uc9d1\ud569\uc744 \uc900\ube44\ud569\ub2c8\ub2e4. \ub370\uc774\ud130\ub294 CSV \ud30c\uc77c\ub85c \uc800\uc7a5\ud558\uac70\ub098, \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0\uc11c \ubd88\ub7ec\uc62c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n BERT\ub97c \uc0ac\uc6a9\ud558\uc5ec \uac01 \ubb38\uc11c\uc758 \uc784\ubca0\ub529\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4:<\/p>\n \uc774\uc81c BERT \uc784\ubca0\ub529\uc744 \uc0ac\uc6a9\ud558\uc5ec CTM\uc744 \uc801\uc6a9\ud569\ub2c8\ub2e4. Gensim \ub77c\uc774\ube0c\ub7ec\ub9ac \ub4f1 \uc5ec\ub7ec \ud1a0\ud53d \ubaa8\ub378\ub9c1 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n CTM\uc758 \uac00\uc7a5 \ud070 \uc7a5\uc810\uc740 BERT\uc758 \ubb38\ub9e5 \uc774\ud574 \ub2a5\ub825\uc744 \ud65c\uc6a9\ud558\uc5ec \ubcf4\ub2e4 \ud48d\ubd80\ud55c \uc8fc\uc81c \uc815\ubcf4\ub97c \uc81c\uacf5\ud55c\ub2e4\ub294 \uc810\uc785\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \ub2e4\uc74c\uacfc \uac19\uc740 \uc774\uc810\uc744 \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n \uadf8\ub7fc\uc5d0\ub3c4 \ubd88\uad6c\ud558\uace0 CTM\uc5d0\ub294 \uba87 \uac00\uc9c0 \ud55c\uacc4\uac00 \uc874\uc7ac\ud569\ub2c8\ub2e4:<\/p>\n \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 BERT\ub97c \uae30\ubc18\uc73c\ub85c \ud55c \ubcf5\ud569 \ud1a0\ud53d \ubaa8\ub378(CTM)\uc744 \uc18c\uac1c\ud588\uc2b5\ub2c8\ub2e4. CTM\uc740 \ub525 \ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud558\uc5ec \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubd84\uc57c\uc5d0\uc11c \uc8fc\uc81c \ubaa8\ub378\ub9c1\uc758 \uc0c8\ub85c\uc6b4 \uac00\ub2a5\uc131\uc744 \uc5f4\uc5b4\uc8fc\ub294 \uae30\ubc95\uc785\ub2c8\ub2e4. \ud5a5\ud6c4 \uc5f0\uad6c\uc5d0\uc11c\ub294 \ub354 \ub2e4\uc591\ud55c \ub370\uc774\ud130\uc14b\uc5d0 \ub300\ud55c \uc5f0\uad6c \ubc0f \uc2e4\uc2dc\uac04 \ucc98\ub9ac \uc801\uc6a9 \uac00\ub2a5\uc131 \ub4f1\uc744 \ud0d0\uad6c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c BERT \uc678\uc5d0\ub3c4 \uc5ec\ub7ec \ub2e4\ub978 \uace0\uae09 \ubaa8\ub378\uc744 \ud65c\uc6a9\ud55c CTM\uc758 \ud655\uc7a5 \uac00\ub2a5\uc131\uc5d0 \ub300\ud574\uc11c\ub3c4 \uc5f0\uad6c\ud558\ub294 \uac83\uc774 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n<\/section>\n1. \uc11c\ub860<\/h2>\n
2. \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uae30\ucd08<\/h2>\n
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3. BERT \ubaa8\ub378\uc758 \uac1c\uc694<\/h2>\n
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4. \ubcf5\ud569 \ud1a0\ud53d \ubaa8\ub378(Combined Topic Models, CTM) \uc18c\uac1c<\/h2>\n
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5. BERT \uae30\ubc18 CTM \uad6c\ud604\ud558\uae30<\/h2>\n
5.1. \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac \uc124\uce58<\/h3>\n
pip install transformers torch<\/code><\/pre>\n5.2. \ub370\uc774\ud130 \uc900\ube44<\/h3>\n
5.3. BERT \uc784\ubca0\ub529 \uc0dd\uc131<\/h3>\n
\nimport torch\nfrom transformers import BertTokenizer, BertModel\n\n# BERT \ubaa8\ub378\uacfc \ud1a0\ud06c\ub098\uc774\uc800 \ub85c\ub4dc\ntokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\nmodel = BertModel.from_pretrained('bert-base-uncased')\n\n# \ubb38\uc11c \ub9ac\uc2a4\ud2b8\ndocuments = [\"\ubb38\uc11c 1 \ub0b4\uc6a9\", \"\ubb38\uc11c 2 \ub0b4\uc6a9\", \"\ubb38\uc11c 3 \ub0b4\uc6a9\"]\n\n# \uc784\ubca0\ub529 \uc0dd\uc131\nembeddings = []\nfor doc in documents:\n input_ids = tokenizer.encode(doc, return_tensors='pt')\n with torch.no_grad():\n outputs = model(input_ids)\n embeddings.append(outputs.last_hidden_state.mean(dim=1))\n<\/code><\/pre>\n5.4. CTM \uc801\uc6a9<\/h3>\n
\nfrom gensim.models import CoherenceModel\nfrom sklearn.decomposition import LatentDirichletAllocation\n\n# CTM\uc744 \uc704\ud55c LDA \ubaa8\ub378 \uc801\ud569\nlda = LatentDirichletAllocation(n_topics=5)\nlda.fit(embeddings)\n\n# \uc8fc\uc81c\uc758 \ud488\uc9c8\uc744 \ud3c9\uac00\ncoherence_model_lda = CoherenceModel(model=lda, texts=documents, dictionary=dictionary, coherence='c_v')\ncoherence_lda = coherence_model_lda.get_coherence()\nprint('Coherence Score:', coherence_lda)\n<\/code><\/pre>\n<\/section>\n6. CTM\uc758 \uc7a5\uc810\uacfc \ud55c\uacc4<\/h2>\n
6.1. \uc7a5\uc810<\/h3>\n
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6.2. \ud55c\uacc4<\/h3>\n
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7. \uacb0\ub860 \ubc0f \ud5a5\ud6c4 \uc5f0\uad6c \ubc29\ud5a5<\/h2>\n