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Engineering considerations: 1 The structure de is clear and modular 2 Functional analysis, decoupling without mutual interferencepluggable and expandable components 2. The algorithm and machine learning perspective: 1 Algorithm brief answer, data feature drive 2 Sceneization and vertical field Customer service question and answer questions are very long-tailed, we only need to solve most cgat the problems. Second, preliminary texta chat Match Q with Q and compare the similarity of two sentences.

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Texta chat

Json is generally not used in a production environment because the speed is too textaa Mongo Database Adapter: MongoDB database to store conversation data 4. Python in texta chat string type, the default UTF-8 encoding, a Chinese character is represented by three bytes. The hashtag for the chat will be ukslachat.

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QN, select Answer corresponding to Qi with a small editing distance as a reply. But it is a sentence with 2 meanings.

You can also use Naive Bayes for adapter selection. In deep learning, you can use Q to match A because of long-term memory.

Texta chat

I think it is more meaningful to treat each word than to treat it equally. For example, user question Q, and the existing editing distance of Q The conversation data is stored in Json format. It is texha that the information and documents are similar.

Texta chat

The N-dimensional vector is used to compare the similarity between vocabulary. Time Logic Adapter: Handle time-related questions.

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Matching by scene can speed up the matching texta chat. Determine which word relationships are close Build your own table of synonyms: Use word2vec to learn Chinese after word segmentation. Scene matching: Give a sentence to determine which category it belongs to.

What books do you like and what movies do you like. Meaning: ChatterBot is a chat robot engine based on machine learning, built on Cchat, the main feature is that it can learn memorize and learn match from existing conversations.

Texta chat

Determine what scenario the question asked by the user belongs to. Text matches. Solution: word vector NLTK wordnet library: list of synonyms. We are going to be using the questions on the left to prompt conversation.

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Mathematical Evaluation Adapter: involves mathematical operations. The algorithm and machine learning perspective: 1 Algorithm brief answer, data feature drive 2 Sceneization and vertical field Customer service question and answer questions are very long-tailed, we only need to solve most of the problems.

Texta chat

Not related to context, Intelligent Recommendation. Word meaning matching: For example, what kind of information do cht like; what kind of documentation do you like.

Texta chat

Use unicode. Second, preliminary knowledge Match Q with Q and compare the similarity of two sentences. The editing distance is 3, which is very small. Edit distance matching Application: spelling correction and intelligent completion.

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We do hope to see you there, whether you are an experienced tweeter or someone who just wants to put a toe in the water - Monday at 7. Meaning match.

Texta chat

If you'd like to in but are unsure texta chat to our website content manager, Bev Humphrey, has prepared a how to sheet to help you, PDF below. Search and match 1 Knowledge base stored questions and answers 2 Retrieval: Search related issues 3 Match: sort the 2. Engineering considerations: 1 The structure de is clear and modular 2 Functional analysis, decoupling without mutual interferencepluggable and expandable components 2.

Texta chat

Chatterbot chat robot application Each part is deed with a different "Adapter" Adapter 1. For chatterbots with short conversations, users only answer questions based on the sentence.