The impact of lemmatization for morphologically-rich languages Abstract Are there ways to improve the performance of language models, beyond increases in size -both in the number of model parameters or in the size of training corpora? Our benchmarks show that another...
The case for evaluation of NLU platforms Synthetic image and video have proven to be a big success for cost-cutting. Synthetic text is following suit: tabular data (that is the data organized in a table with rows and columns) is becoming mainstream already, and the...
What Is Synthetic training data? Synthetic Training data is the data that is used to train an NLU engine. An NLU engine allows chatbots to understand the intent of user queries. The training data is enriched by data labeling or data annotation, with information about...
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...
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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