Welcome to Part 2 of How to use Elasticsearch for Natural Language Processing and Text Mining. It’s been some time since Part 1, so you might want to brush up on the basics before getting started. This time we’ll focus on one very important type of query for Text Mining.
ElasticSearch is a search engine and an analytics platform. But it offers many features that are useful for standard Natural Language Processing and Text Mining tasks. 1. Preprocessing (Normalization) Have you ever used the _analyze endpoint? As you know ElasticSearch has over 20 language-analyzers built in. What is an analyzer
Success stories of how data-driven practices can revitalise businesses are rife today, but there are few as compelling as the story of Ford. In 2006, the legendary car manufacturers were in trouble; they closed the year with a $12.6 billion loss, the largest in the company’s history. As we reported
Text mining innovators-in-the-making MonkeyLearn have finally opened their beta version for the public to sign up. The announcement came at TechCrunch Disrupt in San Francisco, on Monday. The cloud-based artificial intelligence platform intends to transform text mining the same way WordPress made content creation available to all, reports VentureBeat. CEO