{"id":41282,"date":"2022-04-21T09:15:32","date_gmt":"2022-04-21T08:15:32","guid":{"rendered":"https:\/\/developer.kore.ai\/v10-2\/?p=41282"},"modified":"2022-04-21T09:15:52","modified_gmt":"2022-04-21T08:15:52","slug":"update-nlp-configurations","status":"publish","type":"post","link":"https:\/\/developer.kore.ai\/v10-2\/docs\/bots\/api-guide\/update-nlp-configurations\/?lang=ko","title":{"rendered":"NLP \uc124\uc815 \uc5c5\ub370\uc774\ud2b8"},"content":{"rendered":"
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NLP \uc784\uacd7\uac12 \ubc0f \uc124\uc815\uc744 \uc5c5\ub370\uc774\ud2b8\ud569\ub2c8\ub2e4<\/p>\n

\uc774 API\ub97c \uc0ac\uc6a9\ud558\ub824\uba74 \uc571\uc740 NLP \uc124\uc815<\/em>\uc758 \ubd07 \ube4c\ub354 API \ubc94\uc704\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \ub610\ub294 \ud14c\uc2a4\ud2b8 \ubc0f \ud559\uc2b5<\/em>\uc5d0\uc11c NLP \uc124\uc815<\/em>\uc758 \uad00\ub9ac\uc790 API \ubc94\uc704\uac00 \ud544\uc694\ud569\ub2c8\ub2e4.<\/p>\n

POST<\/b> https:\/\/{{host}}\/api\/public\/bot\/{{BotID}}\/configurations?language={{languageCode}}&groupName={{groupName}}<\/code><\/p>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n

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\ucffc\ub9ac \ub9e4\uac1c \ubcc0\uc218<\/span><\/h2>\n\n\n\n\n\n\n\n\n
\ub9e4\uac1c \ubcc0\uc218<\/b><\/th>\n\ud544\uc218\/\uc120\ud0dd \uc0ac\ud56d<\/b><\/th>\n\uc124\uba85<\/b><\/th>\n<\/tr>\n<\/thead>\n
host<\/td>\n\ud544\uc218<\/td>\n\ud658\uacbd URL(\uc608: https:\/\/bots.kore.ai)<\/td>\n<\/tr>\n
BotID<\/td>\n\ud544\uc218<\/td>\n\ubd07 ID \ub610\ub294 \uc2a4\ud2b8\ub9bc ID. \ubd07\uc758 \uc77c\ubc18 \uc124\uc815 \ud398\uc774\uc9c0\uc5d0\uc11c \uc774\ub97c \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/td>\n<\/tr>\n
languageCode<\/td>\n\ud544\uc218<\/td>\n\uc774\ub7ec\ud55c \uc124\uc815\uc744 \uc5c5\ub370\uc774\ud2b8\ud574\uc57c \ud558\ub294 \ubd07 \uc5b8\uc5b4\uc785\ub2c8\ub2e4.<\/td>\n<\/tr>\n
groupName<\/td>\n\ub2e4\uc911 ML \ubaa8\ub378\uc5d0 \ud544\uc694<\/td>\nGroupName\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud2b9\uc815 \uadf8\ub8f9\uc758 ML \ub9e4\uac1c \ubcc0\uc218\ub97c \uc5c5\ub370\uc774\ud2b8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubd07 \uc218\uc900 \uc758\ub3c4 \ubaa8\ub378 \uc124\uc815 groupName\uc744 \uc5c5\ub370\uc774\ud2b8\ud558\ub824\uba74 \uadf8\ub8f9 \uc774\ub984\uc744 "\ubd07 \uc218\uc900 \uc758\ub3c4 \ubaa8\ub378"\ub85c \uc124\uc815\ud574\uc57c \ud569\ub2c8\ub2e4.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n\r\n\t
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\ubcf8\ubb38 \ub9e4\uac1c \ubcc0\uc218<\/span><\/h2>\n

\ub9e4\uac1c \ubcc0\uc218\ub294 \uc5c5\ub370\uc774\ud2b8\ud574\uc57c \ud558\ub294 \uc784\uacd7\uac12 \uc124\uc815\uc5d0 \ub530\ub77c \ub2ec\ub77c\uc9d1\ub2c8\ub2e4. \ub2e4\uc74c\uc740 \ub2e4\uc591\ud55c \uc784\uacd7\uac12 \uc124\uc815\uc5d0 \ub300\ud55c \uc804\uccb4 \ub9e4\uac1c \ubcc0\uc218 \ubaa9\ub85d\uc785\ub2c8\ub2e4.<\/p>\n

\uc124\uc815 \uc5c5\ub370\uc774\ud2b8<\/span><\/h3>\n

\uba38\uc2e0 \ub7ec\ub2dd \uc5d4\uc9c4<\/h4>\n

\uc774 \uc139\uc158\uc5d0\uc11c\ub294 \uba38\uc2e0 \ub7ec\ub2dd \uc5d4\uc9c4\uacfc \uad00\ub828\ub41c \uc124\uc815\uc744 \ub2e4\ub8f9\ub2c8\ub2e4. \uc124\uc815\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uc5ec\uae30\ub97c \ucc38\uc870\ud558\uc138\uc694<\/a>.<\/p>\n

{\r\n    \"configurations\": [\r\n        {\r\n            \"mode\": \"ml\",               \/\/ Machine Learning Engine\r\n            \"exactMatchThreshold\": 90,  \/\/ ML Definitive Score - value in range [80-100]\r\n            \"minThreshold\": 0.4,        \/\/ ML threshold - value in range [0-1]\r\n        }\r\n    ],\r\n    \"mlParams\": {\r\n        \"intentParams\": {\r\n            \"useSynonyms\": true,       \/\/ Bot Synonyms \r\n            \"useStopwords\": true,      \/\/ Stopwords \r\n            \"usePlaceholders\": true,   \/\/ Entity Placeholders \r\n            \"features\": \"n_gram\"       \/\/ Feature Extraction - value in range [skip_gram, n_gram]\r\n            \"skip_gram\": {             \/\/ features should be 'skip_gram'\r\n                \"seqLength\": 2,        \/\/ Sequence Length - value in range [2-4]\r\n                \"maxSkipDistance\": 1   \/\/ Maximum Skip Distance - value in range [1-3]\r\n              },\r\n            \"ngram\": 3,                \/\/ ngram Sequence Length - value in range [1-4]\r\n                                       \/\/ features should be \u2018n_gram\u2019\r\n        },\r\n        \"nerParams\": {\r\n            \"type\": \"corenlp\"          \/\/ NER Model\r\n                                       \/\/ could be \"corenlp\" for  Conditional Random Field \r\n                                       \/\/       or \"spacy\" -  Deep Neural Network\r\n         }\r\n    }\r\n}<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n\r\n\t
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Fundamental Meaning Engine<\/h4>\n
\uc774 \uc139\uc158\uc5d0\uc11c\ub294 \uc5d4\uc9c4\uc758 \uae30\ubcf8 \uc758\ubbf8\uc640 \uad00\ub828\ub41c \uc124\uc815\uc744 \ub2e4\ub8f9\ub2c8\ub2e4. \uc124\uc815\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uc5ec\uae30\ub97c \ucc38\uc870\ud558\uc138\uc694<\/a>.<\/p>\n
{\r\n    \"configurations\": [\r\n        {\r\n            \"mode\": \"cs\",            \/\/ Fundamental Meaning Engine\r\n            \"labelMatch\": true       \/\/ Intent Detection using Task Name Words\r\n            \"isFMThreshold\": true,   \/\/FM Threshold\r\n            \"fmThreshold\": 15        \/\/FM Threshold value\r\n        }\r\n  ]\r\n}<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n\r\n\t
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\uc9c0\uc2dd \uadf8\ub798\ud504 \uc5d4\uc9c4<\/h4>\n
\uc774 \uc139\uc158\uc5d0\uc11c\ub294 \uc9c0\uc2dd \uadf8\ub798\ud504 \uc5d4\uc9c4\uacfc \uad00\ub828\ub41c \uc124\uc815\uc744 \ub2e4\ub8f9\ub2c8\ub2e4. \uc124\uc815\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uc5ec\uae30\ub97c \ucc38\uc870\ud558\uc138\uc694<\/a>.<\/p>\n
{\r\n    \"configurations\": [ THRESHOLDS & CONFIGURATIONS \r\n         {\r\n            \"mode\": \"faq\",  \r\n            \"autoSpellCorrectEnabled\": true,             \/\/ Auto Correction\r\n            \"useBotSynonyms\": true,                      \/\/ Bot Synonyms\r\n            \"enPatternLemma\": false,                     \/\/ Lemmatization using Parts of Speech\r\n            \"pathCoverage\": 50,                          \/\/ Path Coverage - value in range [0-100]\r\n            \"exactMatchThreshold\": 95,                   \/\/ Minimum and Definitive Level for Knowledge Tasks \r\n                                                         \/\/ value in range [0-100] \r\n                                                         \/\/ should be more than minThreshold & maxThreshold\r\n            \"maxThreshold\": 80,                          \/\/ Probable range for Knowledge Task \r\n                                                         \/\/ value in range [0-100] \r\n                                                         \/\/ should be between minThreshold & exactMatchThreshold \r\n            \"minThreshold\": 60,                          \/\/ Low confidence range for Knowledge Task \r\n                                                         \/\/ value in range [0-100] \r\n                                                         \/\/ should be less than maxThreshold & exactMatchThreshold  \r\n            \"suggestionsCount\": 3,                       \/\/ KG suggestionsCount | [0-5]\r\n            \"taskMatchTolerance\": 35,                    \/\/ Proximity of Suggested Matches | [0-50]\r\n            \"longResponses\": {\r\n                \"readMore\": true,                        \/\/ Manage Long Responses\r\n                \"useCustomReadMoreURL\": true,            \/\/ readMore should be true\r\n                \"customReadMoreURL\": \"www.siteurl.com\"   \/\/ readMore link; readMore should be true\r\n              },\r\n            \"searchInAnswer\": {\r\n                \"enabled\": true,                         \/\/  Search in Answer\r\n                \"notifyUser\": true,                      \/\/ Inform end user that it is a probable answer\r\n                \"responseType\": \"relevantWithReadMore\",  \/\/ can be \"complete\" - Show complete response, \r\n                                                         \/\/      or \"relevant\" - Show only the relevant paragraph,\r\n                                                         \/\/      or \"relevantWithReadMore\" - Show only the relevant paragraph with \u201cread more\u201d link ]\r\n                \"customReadMoreURL\": \"www.siteurl.com\",  \/\/ \u201cread more\u201d link \r\n                \"useCustomReadMoreURL\": true             \/\/ enabled should be true\r\n            }\r\n            \"qualifyContextualPaths\": false,             \/\/ Qualify Contextual Paths\r\n        }\r\n ]\r\n}\r\n<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n\r\n\t
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\uc21c\uc704 \ubc0f \ud574\uacb0 \uc5d4\uc9c4<\/h4>\n
\uc774 \uc139\uc158\uc5d0\uc11c\ub294 \uc21c\uc704 \ubc0f \ud574\uacb0 \uc5d4\uc9c4\uacfc \uad00\ub828\ub41c \uc124\uc815\uc744 \ub2e4\ub8f9\ub2c8\ub2e4. \uc124\uc815\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uc5ec\uae30\ub97c \ucc38\uc870\ud558\uc138\uc694<\/a>.<\/p>\n
{\r\n    \"configurations\": \r\n        {\r\n            \"mode\": \"rr\",                 \/\/ Ranking and Resolver Engine\r\n            \"taskMatchTolerance\": 2,      \/\/ Proximity of Probable Matches - value in range [0-20]\r\n            \"useDependencyParser\": true,  \/\/ Dependency Parsing Model \r\n            \"minMatchVal\": 0.4,           \/\/ Minimum Match Score - value in range [0-1] \r\n                                          \/\/ useDependencyParser should be true\r\n            \"rankingParameters\": \"\"       \/\/  Advanced Configurations                                           \r\n                                          \/\/ useDependencyParser should be true\r\n            \"intentRescoring\": false,     \/\/ Rescoring of Intents\r\n            \"isPreferDefinitiveMatch\": true \/\/ Prefer Definitive Matches\r\n        }\r\n ]\r\n}\r\n<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n\r\n\t
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\uace0\uae09 NLP \uc124\uc815<\/h4>\n
\uc774 \uc139\uc158\uc5d0\uc11c\ub294 \uc790\uc5f0\uc5b4 -> \ud559\uc2b5\uc758 \uace0\uae09 NLP \uc124\uc815 \uc139\uc158\uc5d0 \ub098\uc640 \uc788\ub294 \uc124\uc815\uc744 \ucc38\uc870\ud569\ub2c8\ub2e4. \uc124\uc815\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uc5ec\uae30\ub97c \ucc38\uc870\ud558\uc138\uc694<\/a>. \ub2e4\uc74c\uc740 \uc704\uc5d0\uc11c \uc5b8\uae09\ud55c \uace0\uae09 NLP \uad6c\uc131\uc744 \uc124\uc815\ud558\uae30 \uc704\ud55c \uc0d8\ud50c \uc694\uccad\uc785\ub2c8\ub2e4.<\/p>\n
{\r\n    \"advancedNLPSettings\":[\r\n        {\r\n            \"configurationKeyName\": \"NoneIntent\",\r\n            \"configurationValue\":true,\r\n            \"nlpEngine\":\"ML\"\r\n        }\r\n    ]\r\n}\r\n<\/pre>\n
\ub2e4\uc74c\uc740 \ud5c8\uc6a9 \uac00\ub2a5\ud55c \uace0\uae09 NLP \uc124\uc815 \ubc0f \uac00\ub2a5\ud55c \uac12\uc758 \uc804\uccb4 \ubaa9\ub85d\uc785\ub2c8\ub2e4. \ubcf5\ud569\uc5b4 \ubd84\ud560<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Split Compound Words\",\r\n        \"configurationKeyName\": \"splitCompoundWords\",\r\n        \"desc\": \"The settings enables splitting of the compound words into multiple stems and then process the individual stem\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"Boolean\",\r\n        \"range\": [true, false],\r\n        \"defaultValue\": false,\r\n        \"requiresTraining\": true,\r\n        \"language\": [\"de\", \"nl\"],\r\n        \"isChild\": false\r\n    }\r\n<\/pre>\n
\uc758\ub3c4 \uc5c6\uc74c<\/strong><\/p>\n
{\r\n        \"configurationName\": \"None Intent\",\r\n        \"configurationKeyName\": \"NoneIntent\",\r\n        \"desc\": \"Once enabled, a None intent is created which reduces the chances of getting a false positive for an intent match using ML engine\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"Boolean\",\r\n        \"range\": [true, false],\r\n        \"defaultValue\": true,\r\n        \"requiresTraining\": true,\r\n        \"language\": \"ALL\",\r\n        \"isChild\": false\r\n    }\r\n<\/pre>\n
\ucf54\uc0ac\uc778 \uc720\uc0ac\ub3c4 \uac10\uc18c<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Cosine similarity dampening\",\r\n        \"configurationKeyName\": \"cosineSimilarityDampening\",\r\n        \"desc\": \"Avoid penalty on short length questions using Cosine Similarity Dampening\",\r\n        \"nlpEngine\": \"KG\",\r\n        \"dataType\": \"Boolean\",\r\n        \"range\": [true, false],\r\n        \"defaultValue\": true,\r\n        \"requiresTraining\": false,\r\n        \"language\": \"ALL\",\r\n        \"isChild\": false\r\n    }\r\n<\/pre>\n
\ub124\ud2b8\uc6cc\ud06c \uc720\ud615<\/strong><\/p>\n
{\r\n        \"configurationName\" : \"Network Type\",\r\n        \"configurationKeyName\" : \"network\",\r\n        \"desc\" : \"Networks available for intent training\",\r\n        \"nlpEngine\" : \"ML\",\r\n        \"dataType\" : \"enum\",\r\n        \"range\" : [\"Standard\",\"MLP-BOW\",\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\", \"KoreBERT\"],\r\n        \"defaultValue\": \"Standard\",\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : false\r\n    }\r\n<\/pre>\n
\uc5d0\ud3ec\ud06c(Epoch)<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Epochs\",\r\n        \"configurationKeyName\": \"epochs\",\r\n        \"desc\": \"Number of iterations in training the model\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"Number\",\r\n        \"range\": [20, 300],\r\n        \"defaultValue\": 20,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-BOW\",\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\",\"KoreBERT\"]\r\n    }\r\n<\/pre>\n
\ubc30\uce58 \ud06c\uae30<\/strong><\/p>\n
{\r\n        \"configurationName\" : \"Batch Size\",\r\n        \"configurationKeyName\" : \"batch_size\",\r\n        \"desc\" : \"Number of training samples used for each batch while training\",\r\n        \"nlpEngine\" : \"ML\",\r\n        \"dataType\" : \"Number\",\r\n        \"range\" : [10,30],\r\n        \"defaultValue\":10,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-BOW\",\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\",\"KoreBERT\"]\r\n    }\r\n<\/pre>\n
\ud559\uc2b5\ub960<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Learning rate\",\r\n        \"configurationKeyName\": \"lr\",\r\n        \"desc\": \"Learning rate is a hyper-parameter that controls how much we are adjusting the weights of our network with respect to the loss gradient\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"enum\",\r\n        \"range\": [1e-4, 1e-3, 1e-2],\r\n        \"defaultValue\": 1e-3,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-BOW\",\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\",\"KoreBERT\"]\r\n    }\r\n<\/pre>\n
Dropout<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Dropout\",\r\n        \"configurationKeyName\": \"dropout\",\r\n        \"desc\": \"Regularization parameter to avoid overfitting of the model\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"Number\",\r\n        \"range\": [0, 0.8],\r\n        \"defaultValue\": 0,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-BOW\",\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\", \"KoreBERT\"]\r\n    }\r\n<\/pre>\n
\ubca1\ud130\ud654<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Vectorizer\",\r\n        \"configurationKeyName\": \"vector_type\",\r\n        \"desc\": \"Feature extraction technique on training data\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"enum\",\r\n        \"range\": [\"count\", \"tfidf\"],\r\n        \"defaultValue\": \"count\",\r\n        \"requiresTraining\": true,\r\n        \"language\": \"ALL\",\r\n        \"isChild\": true,\r\n        \"parentConfiguration\": \"network\",\r\n        \"requiredParentInput\": [\"MLP-BOW\"]\r\n    }\r\n<\/pre>\n
\ucd5c\ub300 \uc2dc\ud000\uc2a4 \uae38\uc774<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Maximum sequence length\",\r\n        \"configurationKeyName\": \"max_seq_length\",\r\n        \"desc\": \"Length of the training sample or user input\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"Number\",\r\n        \"range\": [10, 30],\r\n        \"defaultValue\": 20,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\",\"KoreBERT\"]\r\n    }\r\n<\/pre>\n
\uc784\ubca0\ub529 \uc720\ud615<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Embeddings Type\",\r\n        \"configurationKeyName\": \"word_embedding_type\",\r\n        \"desc\": \"Feature extraction technique on training data\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"enum\",\r\n        \"range\": [\"generated\", \"pretrained\", \"random\"],\r\n        \"defaultValue\": \"random\",\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\", \"KoreBERT\"]\r\n    }\r\n<\/pre>\n
\uc784\ubca0\ub529 \ucc28\uc6d0<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Embeddings Dimensions\",\r\n        \"configurationKeyName\": \"embedding_dim\",\r\n        \"desc\": \"Embeddings Dimensions to be used in featurization\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"Number\",\r\n        \"range\": [100, 400],\r\n        \"defaultValue\": 300,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-WordEmbeddings\",\"LSTM\",\"CNN\", \"KoreBERT\"]\r\n    }\r\n<\/pre>\n
K Fold \uad50\ucc28 \uac80\uc99d<\/strong><\/p>\n
{\r\n        \"configurationName\" : \"kfold\",\r\n        \"configurationKeyName\" : \"kfold\",\r\n        \"desc\" : \"kfold parameter for Crossvalidation\",\r\n        \"nlpEngine\" : \"ML\",\r\n        \"dataType\" : \"Number\",\r\n        \"range\" : [2,10],\r\n        \"defaultValue\": 5,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : false\r\n    }\r\n<\/pre>\n
\uc758\ub3c4 \uc774\ub984\uc73c\ub85c\uc11c\uc758 FAQ \uc774\ub984<\/strong><\/p>\n
{\r\n        \"configurationName\": \"FAQ Name as Intent Name\",\r\n        \"configurationKeyName\": \"FAQ_Name_Intent_Name\",\r\n        \"desc\": \"Enable to use FAQ Name as Intent Name. \",\r\n        \"nlpEngine\": \"KG\",\r\n        \"dataType\": \"Boolean\",\r\n        \"range\": [true, false],\r\n        \"defaultValue\": false,\r\n        \"requiresTraining\" : false,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : false\r\n    }\r\n<\/pre>\n
\ud37c\uc9c0 \ub9e4\uce58<\/strong><\/p>\n
{\r\n        \"configurationName\" : \"Fuzzy Match\",\r\n        \"configurationKeyName\" : \"fuzzyMatch\",\r\n        \"desc\" : \"This setting enables the use of the fuzzy matching algorithm for intent identification\",\r\n        \"nlpEngine\" : \"ML\",\r\n        \"dataType\" : \"Boolean\",\r\n        \"range\" : [true,false],\r\n        \"defaultValue\": true,\r\n        \"requiresTraining\" : false,\r\n        \"language\" : \"ALL\",\r\n        \"isChild\" : false\r\n    }\r\n<\/pre>\n
\ubd80\uc815\uc5b4 \ucc98\ub9ac<\/strong><\/p>\n
{\r\n        \"configurationName\" : \"Handle Negation\",\r\n        \"configurationKeyName\" : \"f_negation\",\r\n        \"desc\" : \"This setting enables the handling of negated words in intent identification\",\r\n        \"nlpEngine\" : \"ML\",\r\n        \"dataType\" : \"Boolean\",\r\n        \"range\" : [true,false],\r\n        \"defaultValue\": true,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : [\"en\", \"es\"],\r\n        \"isChild\" : false\r\n    }\r\n<\/pre>\n
\ub2e4\uc911 \ubc1c\uc0dd \ubb34\uc2dc<\/strong><\/p>\n
{\r\n        \"configurationName\" : \"Ignore Multiple occurences\",\r\n        \"configurationKeyName\" : \"binary\",\r\n        \"desc\" : \"This setting enables to just use presence or absence of a term instead of the raw counts\",\r\n        \"nlpEngine\" : \"ML\",\r\n        \"dataType\" : \"Boolean\",\r\n        \"range\" : [true,false],\r\n        \"defaultValue\": false,\r\n        \"requiresTraining\" : true,\r\n        \"language\" : [\"en\"],\r\n        \"isChild\" : true,\r\n        \"parentConfiguration\" : \"network\",\r\n        \"requiredParentInput\" : [\"MLP-BOW\"]\r\n    }\r\n<\/pre>\n
\uc0ac\uc6a9\uc790 \ubc1c\ud654\uc758 \uc5d4\ud2f0\ud2f0 \ud50c\ub808\uc774\uc2a4\ud640\ub354<\/strong><\/p>\n
{\r\n        \"configurationName\": \"Test PlaceHolders\",\r\n        \"configurationKeyName\": \"TestPlaceHolders\",\r\n        \"desc\": \"Enable to replace entity values present in the user input with the corresponding entity placeholders during prediction\",\r\n        \"nlpEngine\": \"ML\",\r\n        \"dataType\": \"Boolean\",\r\n        \"range\": [true, false],\r\n        \"defaultValue\": true,\r\n        \"requiresTraining\": false,\r\n        \"language\": \"ALL\",\r\n        \"isChild\": false\r\n    }\r\n<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
<\/div><\/div>\r\n\t
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\uc124\uc815 \uc0ad\uc81c<\/span><\/h3>\n
\uc124\uc815\uc744 \uc0ad\uc81c\ud558\ub824\uba74 \uc704 \uc139\uc158\uc5d0\uc11c \uc5b8\uae09\ud55c \uc124\uc815 \uc774\ub984\uc744 \ub2e4\uc74c\uacfc \uac19\uc774 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n
curl --location -g --request POST \\\r\n  'https:\/\/{{host}}\/api\/public\/bot\/{{bot-id}}\/configurations?language={{languageCode}}' \\\r\n  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \\\r\n  --header 'content-type: application\/json' \\\r\n  --data-raw '{\r\n    \"delete\": {\r\n        \"advancedNLPSettings\": [\r\n            \"kfold\"\r\n        ]\r\n    }\r\n}'\r\n<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
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\uc124\uc815 \uc7ac\uc124\uc815<\/span><\/h3>\n
\uc124\uc815\uc744 \uc7ac\uc124\uc815\ud558\ub824\uba74 \uc704 \uc139\uc158\uc5d0\uc11c \uc5b8\uae09\ud55c \uc124\uc815 \uc774\ub984\uc744 \ub2e4\uc74c\uacfc \uac19\uc774 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n
curl --location -g --request POST \\\r\n  'https:\/\/{{host}}\/api\/public\/bot\/{{bot-id}}\/configurations?language={{languageCode}}' \\\r\n  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \\\r\n  --header 'content-type: application\/json' \\\r\n  --data-raw '{\r\n      \"reset\": {\r\n         \"faq\": [\r\n             \"pathCoverage\",                \/\/ Path Coverage\r\n             \"suggestionsCount\",            \/\/ KG suggestionsCount\r\n             \"minimumAndDefinitiveLevels\",  \/\/ Minimum and Definitive Level for Knowledge Tasks (will reset all three values)\r\n             \"taskMatchTolerance\"           \/\/ Proximity of Suggested Matches\r\n        ],\r\n        \"ml\": [\r\n            \"exactMatchThreshold\",          \/\/ ML Definitive Score \r\n            \"minThreshold\"                  \/\/ ML threshold \r\n        ],\r\n        \"rr\": [\r\n            \"taskMatchTolerance\",           \/\/ Proximity of Probable Matches\r\n            \"minMatchVal\"                   \/\/ Minimum Match Score\r\n        ],\r\n        \"mlParams\": [\r\n            \"ngram\",                        \/\/ ngram Sequence Length\r\n            \"seqLength\",                    \/\/ Sequence Length\r\n            \"maxSkipDistance\"               \/\/ Maximum Skip Distance\r\n        ]\r\n    }\r\n}'\r\n<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
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\uad8c\ud55c \ubd80\uc5ec<\/span><\/h2>\n
\ub2e4\uc74c\uacfc \uac19\uc774 \ud5e4\ub354\uc5d0 JWT\uc640 API\ub97c \ud638\ucd9c\ud569\ub2c8\ub2e4. auth: {{JWT}}<\/code><\/p>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
<\/div><\/div>\r\n\t
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\ucf58\ud150\uce20 \uc720\ud615 \uc751\ub2f5<\/span><\/h2>\n
application\/json<\/code><\/p>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
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\uc0d8\ud50c \uc694\uccad<\/span><\/h2>\n
curl --location -g --request POST \\\r\n  'https:\/\/{{host}}\/api\/public\/bot\/{{bot-id}}\/configurations?language={{languageCode}}' \\\r\n  --header 'auth: YOUR_JWT_ACCESS_TOKEN' \\\r\n  --header 'content-type: application\/json' \\\r\n  --data-raw '{\r\n    \"advancedNLPSettings\": [\r\n        {\r\n            \"configurationKeyName\": \"NoneIntent\",\r\n            \"configurationValue\": true,\r\n            \"nlpEngine\": \"ML\"\r\n        }\r\n    ],\r\n    \"configurations\": [\r\n        {\r\n            \"mode\": \"ml\",\r\n            \"exactMatchThreshold\": 85,\r\n            \"useDependencyParser\": true,\r\n            \"minThreshold\": 0.2\r\n        },\r\n        {\r\n            \"mode\": \"faq\",\r\n            \"useBotSynonyms\": true,\r\n            \"searchInAnswer\": {\r\n                \"enabled\": true,\r\n                \"notifyUser\": false,\r\n                \"responseType\": \"relevantWithReadMore\",\r\n                \"customReadMoreURL\": \"aa\",\r\n                \"useCustomReadMoreURL\": true\r\n            }\r\n        }\r\n    ],\r\n    \"mlParams\": {\r\n        \"intentParams\": {\r\n            \"features\": \"skip_gram\",\r\n            \"skip_gram\": {\r\n                \"seqLength\": 3,\r\n                \"maxSkipDistance\": 2\r\n            }\r\n        }\r\n    },\r\n    \"nlSettings\": {\r\n        \"enableAutoUtteranceAddition\": false,\r\n        \"enableNegativePatterns\": true\r\n    }\r\n}'\r\n<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
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\uc0d8\ud50c \uc751\ub2f5<\/span><\/h2>\n
[\r\n    {\r\n        \"message\": \"Training Queued.\",\r\n        \"Training_ID\": \"5d14b03edba48abcb44375a1\"\r\n    }\r\n]\r\n<\/pre>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>\n","protected":false},"excerpt":{"rendered":"NLP \uc784\uacd7\uac12 \ubc0f \uc124\uc815\uc744 \uc5c5\ub370\uc774\ud2b8\ud569\ub2c8\ub2e4 \uc774 API\ub97c \uc0ac\uc6a9\ud558\ub824\uba74 \uc571\uc740 NLP \uc124\uc815\uc758 \ubd07 \ube4c\ub354 API \ubc94\uc704\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \ub610\ub294 \ud14c\uc2a4\ud2b8 \ubc0f \ud559\uc2b5\uc5d0\uc11c NLP \uc124\uc815\uc758 \uad00\ub9ac\uc790 API \ubc94\uc704\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. POST https:\/\/{{host}}\/api\/public\/bot\/{{BotID}}\/configurations?language={{languageCode}}&groupName={{groupName}} \ucffc\ub9ac \ub9e4\uac1c \ubcc0\uc218 \ub9e4\uac1c \ubcc0\uc218 \ud544\uc218\/\uc120\ud0dd \uc0ac\ud56d \uc124\uba85 host \ud544\uc218 \ud658\uacbd URL(\uc608: https:\/\/bots.kore.ai) BotID \ud544\uc218 \ubd07 ID \ub610\ub294 \uc2a4\ud2b8\ub9bc ID. \ubd07\uc758 \uc77c\ubc18 \uc124\uc815 \ud398\uc774\uc9c0\uc5d0\uc11c \uc774\ub97c \uc561\uc138\uc2a4\ud560 \uc218...","protected":false},"author":22,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17],"tags":[],"class_list":["post-41282","post","type-post","status-publish","format-standard","hentry","category-api-guide"],"_links":{"self":[{"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/posts\/41282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/users\/22"}],"replies":[{"embeddable":true,"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/comments?post=41282"}],"version-history":[{"count":1,"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/posts\/41282\/revisions"}],"predecessor-version":[{"id":41283,"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/posts\/41282\/revisions\/41283"}],"wp:attachment":[{"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/media?parent=41282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/categories?post=41282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/developer.kore.ai\/v10-2\/wp-json\/wp\/v2\/tags?post=41282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}