Topic Detection and Tracking is not an old research area. It was ‘only’ established in the late 90’s and it didn’t really pick up until a few years later. However, a lot has happened since then and today’s research is almost unrecognizable from back then. In this post, I take a brief look at what Topic Detection and Tracking is and at its history.(more…)
In my previous post, I took a look at document-pivot methods in Topic Detection and Tracking. Document-pivot approaches use clustering to find out what people are talking about, but that’s not the only solution. In this post, I take a look at feature-pivot methods, the second type of Topic Detection and Tracking methods. Instead of looking at what people are talking about, these approaches look at how people are talking to detect that something happened.(more…)
Topic Detection and Tracking has been around for more than 20 years, but during this time, there has been a lot of research. When researchers started creating systems, they went off in a few different directions. Earlier, I took a a brief look at Topic Detection and Tracking. In this post I take a look at one of the two main approaches to solving the problem: document-pivot methods.(more…)
This article was originally published on the Times of Malta and appeared in the Sunday Times of Malta on 10 March, 2019. The article is being reproduced as it appeared originally.
One out of every two people watched part of the FIFA World Cup last year. Yet in spite of the sport’s popularity, there is no robot that could sit next to you on a weekend afternoon, sip on a cold beer, and contemplate your team’s woes and successes.
When you sit down in front of a television to watch a football match, you understand what you are watching, but there are many nuances that we take for granted. What would it take for a machine to do the same thing?(more…)