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Have a lot of synonyms of the word and has a lot data.   -Javad Ashrafov

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Have a lot of synonyms of the word and has a lot data.   -Javad Ashrafov

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many different, words and examples, that you can put into the database

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many different, words and examples, that you can put into the database

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(Thats why i was

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Bigger words and more correct word meaning

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Bigger words and more correct word meaning

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It will feel like a human and repeat a user's name and ask them natural sounding question

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It will feel like a human and repeat a user's name and ask them natural sounding question

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The not-so-great training dataset would have false synonyms of the word. And have synonyms that do not match and has less data or has the same word repeated.

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only a few words, not many examples, and 0%-10% correct information.

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only a few words, not many examples, and 0%-10% correct information.

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A successful chatbot would be able detect the emotion of the word in the sentence whether it was positive or not -Javad A

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Good and many different examples, many more words than a "not-so-good" chat bot

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Good and many different examples, many more words than a "not-so-good" chat bot

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A successful chatbot will make good words.

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A successful chatbot will make good words.

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The chatbot would give clear and understandable question.

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Just say hello instead of hello (your name)

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Just say hello instead of hello (your name)

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questions that the user knows what kind of response they should put

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unique types of trainign data

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Many different responses a user can use "yes = yeah, ye, yup, yas, and so on + acronyms such as OMG, WTH, LMAO 

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Many different responses a user can use "yes = yeah, ye, yup, yas, and so on + acronyms such as OMG, WTH, LMAO 

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The user experience of the chatbot

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A "just okay" robot might have some trouble detecting the emotion of the word. It would not respond properly.

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the just okay chatbot

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It will include massive amount of data so the computer would not struggle while detecting. the emotion.

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The way it works and if there are any bugs