Josh Constine of TechCrunch recently shared some of the cooler features of TipSense, a great company from last year’s SemTechBiz Start-Up Competition. Constine writes, “No one wants to read thousands of reviews. You just want answers. Luckily there’s TipSense, a new startup whose algorithm sorts big messy data sets. TipSense’s site DishTip tells you what to order at restaurants, for example, while its AppCrawlr deduces an app’s best and worst features and lays them out with competitors on a comparison chart. TipSense is so smart I bet it gets acquired… or at least fields plenty of buyout offers. That’s because while people won’t shut up about big data, few companies have viscerally proven to consumers why it’s important. David Schorr built and bootstrapped TipSense over the last four years to change that. I met him at SXSW, was very impressed, and he agreed to let me write the first official interview with him about his stealthy startup.” Read more

The semantic technology platform behind restaurant dish discovery service Dishtip (which The Semantic Web Blog discussed here) has made its way to a new domain: mobile apps. The company last week unveiled AppCrawlr, which uses its TipSense content discovery and knowledge extraction technology to cut through the noise to help users find the app that’s right for them in a world of hundreds of thousands of options for iPhone, iPad and Android devices.

“With traditional search models there’s no easy way for guided discovery to narrow down from all the apps out there to what you want,” says Dave Schorr, who with Joel Fisher is a co-founder of TipSense LLC. Keyword searches aren’t going to help you find apps that help when you are having a bad day, for instance, or understand that someone looking for a dating app (as in relationships) is looking for something different than someone looking for a date (as in scheduling and productivity) app. But searches on AppCrawlr can suss those out, taking data from from all across the web – blogs, tweets, reviews, and so on – and surfacing and organizing the concepts and topics buried in all that unstructured data.

“It’s a new paradigm to manage a large data set,” says Schorr. “We’re using concepts to come up with a much better experience for discovery.”

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