Posts Tagged ‘entity recognition’

Discover The Mobile App You Really Want

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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Personal Digital Assistants For Everybody

The Semantic Web Blog mentioned here, there is speculation that the Siri intelligent personal digital assistant technology may come to light in Apple’s fall iOS 5 release. Which is all well and good for users on Apple’s mobile platforms, but myBantu founder and vice president of products and strategy Bharath Yadla sees an opportunity to bring personalized recommendations for entertainment to a wider swath of the populace. The iPhone and Android version of its application, to join its web and Facebook applications. officially launch next week.

“We see absolutely a great opportunity with other platforms from a mobile standpoint,” he says. “And when you leverage the application on Facebook, that is a predominant presence.”

What users are leveraging in this intelligent assistant is its ActiveRelevance platform for providing relevant and personalized recommendations based on their profiles and queries. The platform leverages both artificial intelligence and social relevance, assessing some nine dimensions, including personal interests, proximity of choices, popularity, and peer influence, in order to deliver a handful or two of results. The social relevance comes by way of crowd-sourcing recommendations from sites such as OpenTable and Rotton Tomatoes, friends on social networking platforms, and the output of search as well as semantic engines. Users can enter their requirements in natural language, such as top romantic restaurant nearby, for the ActiveRelevance engine to parse intent and come to some conclusions.

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