Segmentation: splitting queries for bot's better understanding of users

[fa icon="calendar'] May 31, 2018 7:00:00 PM / by Bitext posted in NLP, Bitext, Segmentation

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A client came to us because their bot couldn’t understand customer requests like: “I’ve been a client for five years and my daughter wanted that present so badly; but I haven’t received it yet!". It was impossible for their bot to understand such a combination of knowledge items. That’s how we started implementing query segmentation.

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Bitext, 2018 Cool Vendor in AI Core Technologies by Gartner

[fa icon="calendar'] May 21, 2018 6:55:15 PM / by Bitext posted in NLP, Bitext

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Last week, Bitext was included in the selective list of "Cool Vendors in AI Core Technologies” by Gartner, Inc. We have been recognized for our NLP Middleware technology for conversational bots and virtual assistants.

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What can language identification do for bot builders?

[fa icon="calendar'] May 11, 2018 4:03:00 PM / by Leticia Martín-Fuertes posted in NLP, Chatbots

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For a monolingual person, it comes as an uncomfortable reality that most people in the world (60%) speak more than one language in their day-to-day lives. It is very common that a person who speaks one language at home and then another one outside, be it at school or at work. But many more scenarios are possible.

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Bitext presents... its renewed API platform!

[fa icon="calendar'] May 8, 2018 5:15:00 PM / by Bitext posted in NLP, Bitext

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We can't deny it: our API platform, the longest-standing product we have been offering, is our favorite. Up until now it was fairly good and defintely had the job done, but we knew we could achieve even greater results. So these past few months we have been working intensively on renovation at all levels, and now we are truly excited to present to you a new version!

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Building bots? You can now stop fearing day 1 of production

[fa icon="calendar'] Apr 30, 2018 5:44:39 PM / by Leticia Martín-Fuertes posted in NLP, Chatbots, NLU

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What happens after you build a chatbot for a client? I mean, when the architecture is set up, the NLU module has been built, the conversation flows are designed, and everything is ready. All is left is going into production, where you will have thousands of users' interactions that will train your bot and make it super smart, right?

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