By Daniel Benito, Chief Product Officer at Bitext When implementing conversation flows for a chatbot, one of the most time-consuming tasks is preparing training data for the Natural Language Understanding (NLU) component. This involves coming up with examples of the...
The use of word embeddings has become the standard approach for dealing with text input in AI models. While an extensive research has been carried out during these years to analyze all theoretical underpinnings of algorithms such as word2vec, fastText and BERT, it is...
In recent years, word embeddings have become the de facto input layer for virtually all AI-based NLP tasks. While they have undoubtedly allowed text-based AI to advance significantly, not much effort has gone towards examining the limitations of using them in...
While a lot of research has been devoted to analyzing the theoretical basis of word embeddings, not as much effort has gone towards examining the limitations of using them in production environments Quick intro. Word embeddings are essentially a way to convert text...
The following practices will help you design a great conversation between your chatbots and your clients: Transparency Avoid using an excess of predetermined links and buttons Use an NLP middleware approach Include politeness and small talk Tolerate typos and slightly...
Arabic is a complex language for NLP tasks, even for simple ones like lemmatization. There are several reasons for this: Arabic creates words based on roots: for example, the word کتاب (kitab, “book”) is derived from ك ت ب (k t b). Many related words are derived from...
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