Hungry to discover the top 100 restaurant dishes across the good old USA? Well, have your fill of them over at, which today has debuted a semantic mashup that covers the bases from salted caramel ice cream at San Francisco’s Bi-Rite Creamery to chorizo stuffed dates at Chicago’s Avec to Hirata pork buns at Ippudo NY. Users can filter by type of food (e.g. vegetarian or comfort) and what cuisine, as well as what meal course it fits into, and price. (The list is heavy on the big-city restaurant dishes, admittedly, given that that’s where a lot of the web discussion action is, but as likely to come up with an offering from a vendor street cart as a swank spot.)

The minds behind Dishtip, TipSense LLC founders Joel Fisher and Dave Schorr, say this hasn’t been possible before, and wouldn’t be now without the deep layers of semantic analysis that’s revealing detailed and relevant information based on millions of sources. The list aims to further play out what has been the company’s value proposition to foodies – the ability to search at the level of lobster roll vs. seafood, say, or chicken parm va. Italian food.

“We have all this data now from across the USA and we don’t  think anywhere else is this data aggregated and analyzed on a national scale,” says Fisher. “No one else has been able to do this to test  where the Semantic Web is today, where the capabilities are. We have harnessed vast amounts of information to even understand this kind of data and it gets much, much deeper.”

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