Come see how MCT has wrangled the news industry's Big Data problem by classifying content into very precise, often overlapping concepts.

At MCT, each story gets a set of tags that might denote topics, geography, dates, currencies, companies, the function of the document, and other data points. You’ll learn how searching on those returns highly relevant results that can power mobile apps, websites and research for stories. It’s the difference between finding the last five stories written on exactly the topic you’re looking for and having to sift through a million returns from an Internet search.

News organizations have long had some method of sorting content, the most obvious of which are AP category codes and IPTC codes. These manual sorting processes have helped editors more efficiently find content on broad subjects.

Adding deeper levels of classification lets news organizations automatically push content on specific subjects to mobile users based on user profiles. They can also tailor the reading experience by showing content on web pages that they already know are of interest to individual readers. Content intelligence also helps drive SEO rankings, as current stories can be related to archived content on the same subject. Related tags also can be used to power internal search engines on sites and as an internal library for research on whole stories or parts of news items. Content intelligence is about stemming the flood of content into a digestible and intelligible stream for journalists and readers.

A demo led by MCT-Smartlogic at their station in the Midway