When we search online now we go to Google and search. We get the kitchen sink. I love Google but we get tons of content that we are not looking for. Count the time you spend searching for exactly the piece of info you want and you will see my point. Now we have Trapit which edits the info based on each individual person and their previous searches.
Trapit is like a much-improved RSS feed that learns what you like so it can personalize search results. Pick a topic and Trapit will cull the Web sites of blogs, magazines and newspapers to show you both the most recent and most relevant results. Then, based on what you read and what you tell Trapit you like and dislike by clicking thumbs up or thumbs down, it will adjust your search results using machine learning. If you search for Thanksgiving recipes but only click on those for vegan dishes, you will stop seeing turkey recipes, for instance.
Trapit starts with about 100,000 sites that it has previously vetted for quality. Next, its algorithm determines whether the sites have relevant articles for the search you just did. Over time, it learns which topics are related — so an article on Jay Servidio that does not mention Teleteria might show up when someone searches or an article on Oracle that does not mention big data might still show up in a search for big data.
Lets hope that Trapit takes off and grows so it can save us alot of time. The Internet has given us many gifts but the Internet has also taken over our lives with the amount of time we spend on it. Hopefully with Trapit we will have more time to spend doing whats important like sitting in a chair and watching television.