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...
How Synthetic Text can solve your training and evaluation problems for your virtual assistants / chatbots When shopping online, customers frequently have the need to modify their order: exchanging an item in the basket, deleting something already added… Customers ask...
A couple of weeks ago, Facebook introduced an upgrade for its Messenger platform. The upgrade of Messenger was aimed to improve the user experience. According to the announcement, they have taken into consideration user’s feedback to create new features. It sounds...
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...
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...
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