Some quick reactions to Trap.It

From the same place that gave birth to Siri (the cool app that functions as a personal assistant by listening to what you ask it to do) comes a new search engine called Trap.it. It’s pitched as a “personalized search engine”, but really functions more as a curated information recommendation engine. With trap.it, you create “traps”, which is a stream of recommendations seeded with a keyword search. The idea is that you thumbs up/thumbs down the content given to you, trap.it learns over time, and gives you better results. In concept, it feels quite similar to the now-defunct Twine, built by Nova Spivack. The particulars are very different however. It also bears some striking similarities to Flipboard, although there’s no swiping as this is a web app….

I gave it a few tricky concepts to warm up on. My first test was to get a stream of content about Vikings (the Scandinavian kind, not the football team) – no surprise, given the title of this blog. Since there are two very well defined concepts there, it’s a chance to see how well the learning engine can hone in on the concept, and not the word itself. I got a quick stream of viking stuff, half of which was about the Scandinavians and half the football team. I thumbed down about 4 articles on the Minnesota Vikings, and presto, my stream has become empty of football. Pretty impressive! The main problem now is the stream is mostly full of one news story, about climate change impacting Greenland, with many different sources recapping the same article. So while the concept disambiguation is working, they need a “story disambiguation” similar to what Google News has. I also found it awkward to get more results into the trap – there is an “infinite scroll” option, where as you scroll you get more articles, but my Viking trap could never get more than about 16 or so articles. Not sure whether this is a UI limitation, or whether their base of indexed documents simply doesn’t have more. They also need some way to delete an article from the feed, or mark it as read – the UI suggests that this is a kind of very smart RSS reader, but the basic mechanics of RSS readers are missing….once I’ve read something, I want to get it out of the way.

I tried a couple of other Traps. I’ve been on a binge of listening to “dubstep” recently, which is a trendy new sub-genre of electronic music. I got a great stream of interesting articles, and even found a new musician or two to listen to. The articles were good, but sourced from fairly random-seeming sites – Trap.it is not very clear about how they curate their content sources…..I created a historical fiction trap, and immediately got an interview with Steven Pressfield, one of my favorite historical fiction authors, who has a new book out. Pretty impressive, although likely somewhat accidental? But very cool stuff. This is something to keep an eye on.

(ps – they are pretty responsive to user comments on Twitter @gotrapit – they got back to me almost immediately when I tweeted)

(they may still be in closed beta – GigaOm seems to have some invite codes at the bottom of this article)

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5 thoughts on “Some quick reactions to Trap.It”

  1. Yeah 8) I’ve been checking that out too. Seems more designed for a “multi-player” environment though, to get the most of it.

  2. There’s a service similar to this out there called mygeni(.org) that offers content relevancy and credibility filtering and aggregation. The big difference though is that there it is all user-generated content (anything from articles to sound tracks) and one can filter by friends’ intimacy levels (only content from close friends or content from the public stream and some more options). They take the friendship/relationship with a content item’s poster into account when calculating its relevancy and credibility. With trap.it there doesn’t seem to be any indication of how it is determined what sources are categorized for relevancy and credibility…

  3. Thanks for the pointer Mike. I will check it out. While trap.it indeed doesn’t seem to give any tangible indication of how it finds sources or ranks content, I’ve found it does a pretty good job of surfacing high quality content; I expect the sources are curated by the folks who built the site.

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