The Incredible Potential of Text Analytics – The Use Cases Explained.
New advances in text analytics make the tech news nearly every week, most prominently IBM Watson, but also more recently AI approaches such as ELMo or BERT. And now it made world news with the pandemic caused by the Covid-19 virus, with the white house requesting help via NLP.
Text Analytics and Natural Language Processing (NLP) deal with all types of automatic processing of texts and is often built on top of machine learning or artificial intelligence approaches. The idea of this article is not to explain how text analytics works, but instead to explain what is possible.
OTTERs and the Theory of Automatic Testgeneration
Creating test cases by hand can be a lot of effort. It takes time, and so costs plenty of money. It is estimated that testing on average costs roughly 50% of the project budget.So maybe, we could try and skip it? Well, we still need to test and, among other things, make sure that the system behaves in the way we specified. But maybe we can develop an automatic method for creating tests? And this is the core idea: Why not use the specification to generate the tests?
Natural Language Processing: Timeline Extraction with Regexes and spaCy
New text is generated in a mindblowing speed today. Think about news articles, social media messages, reports, e-mails etc. However, we cannot do much with unstructured text. But as soon as we extract some structured information from