What is the difference between stemming and lemmatization?

[fa icon="calendar'] Jul 7, 2021 8:54:10 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 uses the context in which the word is being used. We'll later go into more detailed explanations and examples.  

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What do you evaluate in your chatbots? Some ideas

[fa icon="calendar'] May 31, 2021 10:00:00 AM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLU, POS tagging, AI, Multilanguage, NLP for Core, NLP for Chatbots, "Multilingual synthetic data"

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In this blog we will discuss three ways of doing your chatbot evaluation by using:

  1. real world evaluation data
  2. synthetic data
  3. "in scope" or "out of scope" queries
You have a chatbot up and running, offering help to your customers. But how do you know whether the help you are providing is correct or not?  Chatbot evaluation can be complex, especially because it is affected by many factors. 
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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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From the eCommerce problem to the chatbot solution: Part II

[fa icon="calendar'] Jan 30, 2020 4:44:17 PM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLG, NLU, AI, Multilanguage, NLP for Chatbots, Finance, Banking, "Multilingual synthetic data"

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A chatbot offers significant advantages: it allows your customer support to be omnichannel —i.e. customers will be able to approach you via written chat, voice chat, email, phone, etc.—; it will save you the costs of hiring many additional employees, while sparing you the need of training agents every time your product changes; your customers’ satisfaction will increase; finally, you will get more and more sales (because well-taken-care-of visitors tend to become loyal and regular customers).

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From the eCommerce problem to the chatbot solution: Part I

[fa icon="calendar'] Jan 28, 2020 4:15:00 PM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLG, NLU, AI, Multilanguage, NLP for Chatbots, Finance, Banking, "Multilingual synthetic data"

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Let’s repeat: more and more people (customers, or prospective customers) prefer eCommerce these days. They have learnt the comfort of buying from their home, without having to take their car or the public transport to personally go and buy at each store. As always, each option has its advantages and disadvantages, but eCommerce has become a common trend now.

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