Chatbots and Customer Service: Why Do Chatbots Fail?

[fa icon="calendar'] May 30, 2019 6:25:00 PM / by Bitext posted in API, Machine Learning, NLP, Semantic Analysis, Sentiment Analysis, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Text Categorization, Artificial Intelligence, Deep Learning, Chatbots, Phrase Extraction, NLU, POS tagging, AI, Entity extraction, NLP for Core

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Although chatbots have become quite popular in recent years, there is still room for improvement. A well-trained chatbot must correctly react to any query sent by a user creating a successful human-like conversation. Is that happening? We don’t think so.


Round-the-clock service, cost reduction and delivering a better customer experience are, among others, the main benefits of chatbots for customer service automation. If you are thinking of setting up a conversational agent to take care of your customers, it’s all-important for you to know not only the bright side, but also the dark one. You just can't spin up a basic chatbot and expect it to work well.

 

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Natural Language Processing (NLP) vs. Machine Learning

[fa icon="calendar'] May 20, 2019 5:06:17 PM / by Bitext posted in API, Machine Learning, NLP, Semantic Analysis, Sentiment Analysis, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Text Categorization, Artificial Intelligence, Deep Learning, Chatbots, Phrase Extraction, NLU, POS tagging, AI, Entity extraction, NLP for Core, NLP for CX

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Two concepts, one mission: to make machines understand humans. Natural Language Processing (NLP) and Machine Learning (ML) are all the rage right now, but people tend to mix them up. In this post, there will be a distinction between these two different but complementary terms in the field of Artificial Intelligence.

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Bitext Meets with Large Corporates in Hamburg

[fa icon="calendar'] May 3, 2019 6:35:00 PM / by Bitext posted in Sentiment Analysis, Bitext, Deep Linguistic Analysis, Artificial Intelligence, Deep Learning, Chatbots, AI, NLP for Core, NLP for Chatbots, Finance, Banking

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On 24 and 25 April 2019, at the old Customs House in Hamburg, Bitext was one of 54 companies backed by the European Innovation Council (EIC) pilot that had the opportunity to pitch and present their business cases and to engage in one-on-one business meetings with representatives from some of the leading Corporates in Europe. The multi-corporate event was promoted by the EIC pilot together with comdirect.

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Artificial Data Is Empowering Deep Learning Applications

[fa icon="calendar'] Apr 22, 2019 5:27:00 PM / by Bitext posted in Deep Linguistic Analysis, Deep Learning, AI, NLP for Core, NLP for Chatbots

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Every time we ask Siri to set a reminder, we use Google Translator or we click on a banner, there are deep learning technologies playing behind the scenes.  But for these to work properly, they need to be trained with a huge amount of quality data.
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What Is Anonymization for and How Will your Business Profit from It?

[fa icon="calendar'] Apr 11, 2019 4:06:54 PM / by Bitext posted in Deep Linguistic Analysis, Deep Learning, AI, NLP for Core, NLP for Chatbots

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By 2021, organizations that bypass privacy requirements and are caught lacking in privacy protection will pay 100% more in compliance costs than competitors that adhere to best practice. (Gartner- Top 10 Strategic Technology Trends for 2019: A Gartner Trend Insight Report).

Applying anonymization techniques to your data can bring some considerable benefits and liberate you from certain obligations set out in GDPR or California Consumer Privacy Act.  Do you know for example that if you want to anonymize new data collected from your website, then you’ll either need to obtain consent to collect personal data (like cookies, IP addresses and device ID) and then apply anonymization techniques, or only collect anonymous data from the start? This is why any business is concerned about anonymization.

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Main Challenges for Word Embeddings: Part II

[fa icon="calendar'] Dec 28, 2018 10:32:29 AM / by Bitext posted in NLP, Deep Linguistic Analysis, Phrase Extraction, POS tagging, NLP for Core

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A ‘word embeddings’ approach has been widely adopted for machine learning processes. While an extensive research has been carried out during these years to analyze all theoretical underpinnings of algorithms such as word2vec, GloVe or fastText, it is surprising that little has been done, in turn, to solve some of the more complex linguistic issues raised when getting down to business.

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