As we get better at teaching machines what to think, we need to get better at teaching them what we think. Real-time classification strategies can help.
Every Supervised Machine Learning process benefits from well-structured training data. eContext’s classifications can automatically annotate and enrich any size corpus, describing relevant features and segmenting data for cleaner modeling.
eContext’s taxonomy is curated by real people, who classify text the way humans do, taking into consideration the nuance of language, contextual meanings, jokes, and popular culture issues that impact meaning.
We’ve created a taxonomy that is 21 tiers deep with 450,000 categories and 55 million vocabulary rules. eContext’s text classification engine pulls data from any source and runs it through our universal topic hierarchy — all in real time. The result is structured data that you can use immediately.
“After extensive tests, eContext was the clear winner. eContext powers VEDO Focus, where our clients are able to classify and enrich a vast amount of data in real time. We are delighted with eContext’s level of depth and accuracy.”
“eContext’s classification helps us understand, in real time, the relevant topics driving conversations across myriad digital properties so that we can provide previously unknown insights to some of the world’s largest companies.”
“Wow — eContext is like named-entity recognition on steroids! In my research, I’ve worked with long-form text for years, including news, surveys, and conversational data, but I’ve never seen it structured and annotated so effectively before. Your algorithms are incredible.”