{"id":18124,"date":"2019-02-12T09:36:25","date_gmt":"2019-02-12T09:36:25","guid":{"rendered":"\/docs\/bots\/bot-builder\/knowledge-graph\/"},"modified":"2021-03-30T08:47:48","modified_gmt":"2021-03-30T07:47:48","slug":"knowledge-graph","status":"publish","type":"post","link":"https:\/\/developer.kore.ai\/v7-2\/docs\/bots\/nlp\/knowledge-graph\/","title":{"rendered":"Knowledge Graph Training"},"content":{"rendered":"
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Training your Bot<\/a> is not restricted to Machine Learning and Fundamental Meaning engines. You need to train the Knowledge Graph engine, too.<\/p>\n

Knowledge Graph engine responds to users\u2019 intents by identifying the appropriate questions from the Knowledge Graph.<\/p>\n

Knowledge Graph<\/span><\/h3>\n

From the Knowledge Graph, follow these steps to build and train the corresponding Knowledge Graph:<\/p>\n

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  1. Identify terms by grouping the unique words in each FAQ question. Build a hierarchy based on all such unique words.<\/li>\n
  2. Associate traits with terms to enable filtering FAQs from multiple identified results.<\/li>\n
  3. Define synonyms for each term\/node in the hierarchy. Ensure that all the different ways to call the term are defined.<\/li>\n
  4. Depending on the importance of each term in a path, mark them as either mandatory or regular.<\/li>\n
  5. Define alternative questions for each FAQ to ensure better coverage.<\/li>\n
  6. Manage Context for accurate response.<\/li>\n
  7. Stop Words can be used to filter unwanted utterances.<\/li>\n<\/ol>\n\r\n\t\t<\/div>\r\n\t<\/div>\r\n
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    Training and testing your Knowledge Graph is crucial to building an efficient Knowledge Graph.<\/p>\n

    Before training, you can improve performance by using tags, synonyms, and traits.<\/p>\n

    Term Type<\/span><\/h3>\n

    (before ver 7.2, this was referred to as Term Usage under Manage Usage)<\/p>\n

    Designate the terms and tags in Knowledge Graph as Default, or Mandatory, or Organizer depending on their importance in qualifying matching paths:<\/p>\n