In a previous post, we conducted a comprehensive benchmark on the role of synthetic text generation for intent detection using traditional Natural Language Understanding (NLU) platforms. In that study, we specifically examined the performance of Rasa as an example,...
We have shown in previous posts why Synthetic Training Data is the best way to boost the accuracy of any chatbot, and the solution to the most important problem of chatbots nowadays: data scarcity, namely, the lack of accurate and useful training data for the problems...
In previous posts, we have outlined the crucial role of Machine Learning for Analytics (in How to Make Machine Learning more Effective using Linguistic Analysis?), and the implications of using Machine Learning for analyzing and structuring text (in How Phrase...
This post dives into one of the topics of a previous post “How to Make Machine Learning more effective using Linguistic Analysis”. We referred to the strong points of Machine Learning technology for insight extraction. We also stated that text analysis is...
Text analysis is becoming a pervasive task in many business areas. Machine Learning is the most common approach used in text analysis, and is based on statistical and mathematical models. Linguistic approaches, which are based on knowledge of language and its...
Everything looks promising in the world of bots: big players are pushing platforms to build them (Google, Amazon, Facebook, Microsoft, IBM, Apple), large retail companies are adopting them (Starbucks, Domino’s, British Airways), press is excited about movies becoming...
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