AI and chatbots: How to design a great conversation?

[fa icon="calendar'] May 11, 2021 5:52:38 PM / by Bitext posted in API, Machine Learning, NLP, Big Data, Bitext, Natural Language, Artificial Intelligence, Deep Learning, Chatbots, Phrase Extraction, NLG, TechCrunch, NLU, AI, Multilanguage, NLP for Core, NLP for Chatbots

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The following practices will help you design a great conversation between your chatbot and your client:

  • Transparency
  • Avoid using an excess of predetermined links and buttons
  • Use an NLP middleware approach
  • Include politeness and small talk
  • Tolerate typos and slightly ambiguous formulations
  • Always include domain specific terminology
  • Define your bot's tone
  • Keep the number of possibilities limited
  • Let the user know when the bot is "thinking" or processing the query

Reducing complicated, confusing processes down to a natural conversation is potentially a huge business opportunity for anyone willing to jump headfirst and create a great user experience. Chatbots are only as smart as the words you feed them. If a bot is too rudimentary, people will lose trust in the company and will feel ignored and unappreciated. UX problems appear when the user deviates from the designed linear flow.

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What is the difference between stemming and lemmatization?

[fa icon="calendar'] Apr 5, 2021 4:35:03 PM / by Bitext posted in Machine Learning, NLP, Bitext, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, Stemming, AI, Multilanguage, Lemmatization, NLP for Core, NLP for Chatbots, Conversational AI

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Stemming and lemmatization are methods used by search engines and chatbots to analyze the meaning behind a word. Stemming uses the stem of the word while lemmatization, the context in which the word is being used. We'll later go into more detailed explanations and examples.  

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Why is Bitext's Text Generation Unique?

[fa icon="calendar'] Nov 16, 2020 7:15:12 PM / by Bitext posted in Machine Learning, NLP, Bitext, Natural Language, Artificial Intelligence, Deep Learning, Chatbots, NLG, Multilanguage

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NLU vs. ITR Chatbots... Which one should I use?

[fa icon="calendar'] Oct 15, 2020 5:03:33 PM / by Bitext posted in Machine Learning, NLP, Natural Language, Artificial Intelligence, Chatbots, NLU, AI, NLP for Chatbots

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Noisy text is realistic text

[fa icon="calendar'] Feb 24, 2020 4:45:00 PM / by Bitext posted in API, Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, NLG, NLU, Query Rewriting, AI, Multilanguage, NLP for Core, NLP for Chatbots, NLP for CX, "Multilingual synthetic data"

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One of the flaws of usual training data generation is that, when you ask somebody to manually create training data for you, they will make an effort to write these sentences correctly, following the spelling and punctuation norms of your language. Even if some errors appear, they will be minimal, because they are trying to do things right —this is, to provide “orthographically right” sentences.

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Linguistic Resources in +100 Languages & Variants

[fa icon="calendar'] Feb 11, 2020 2:55:24 PM / by Bitext posted in API, Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, NLG, Stemming, NLU, AI, Multilanguage, Language Identification, Decompounding, Lemmatization, NLP for Core, Finance, Banking

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All Machine Learning (ML) engines that work with text can benefit from a solid linguistic background. If they are working in a multilingual environment, the need of a good lexicon (with forms, lemmas and attributes) is overwhelming. Even so, basic features such as Word Embeddings hugely improve when enriched with linguistic knowledge, and if this is not usually applied, is because of a lack of linguists working for ML companies.

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