All Machine Learning (ML) engines that work with text can benefit from a solid linguistic background. If they are working in a multilingual environment, the need of a good lexicon (with forms, lemmas and attributes) is overwhelming. Even so, basic features such as Word Embeddings hugely improve when enriched with linguistic knowledge, and if this is not usually applied, is because of a lack of linguists working for ML companies.
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Powered by a linguistic approach, the future of natural language processing will enable human-like understanding through a wide range of applications. Thanks to Bitext NLP technologies, that far future is closer than expected. Bitext solutions are fully oriented to the current needs of many forward-looking companies relying on cutting-edge techniques ranging from sentiment analysis tools to a generation of artificial training data. After years of hard work in the field of the automation of customer support, Bitext developed the most advanced API ever seen and several conversational agents for innovative enterprises as, for instance, TechCrunch.
When we are running a search, we want to find relevant results not only for the exact expression we typed on the search bar, but also for the other possible forms of the words we used. For example, it’s very likely we will want to see results containing the form “skirt” if we have typed “skirts” in the search bar.