When it comes to finding the perfect restaurant, hotel or entertainment venue, chances are you turn to one or more user reviews sites. After all, if you're going to trust anything, why not trust testimonials from a business' past customers?
User reviews, of course, aren't perfect, and sorting through them can require a lot of effort. Hence the effort many companies are making to build recommendation engines that use computing power to tell you where you should eat your next meal or go to have a good time.
The latest entrant into the recommendation engine space is a startup called Nara, which just raised $4m in angel funding.
The company, which is staffed by numerous PhDs, has developed neural networking technology it calls the 'Nara Neural Network.' In short, it's supposed to function like the human brain, which, of course, can often be quite good at taking in limited amounts of information and extrapolating from that information much larger conclusions.
So how does Nara plan to apply this technology in the real world? TheNextWeb's Alex Wilhelm explains:
When you sign up for Nara, you select a town, and then give it three names, the names of three restaurants. From there, it recommends other places that you might like. From three pieces of data, it tries to generate a list that you can use. From its beta website, Nara claims to have "50,000 restaurants in 8 cities" in its database. Drop down menus reveal that the company is working next on shopping, hotels, and other entertainment. Currently, places to eat are its only game.
Can Nara, with three restaurant names, make better recommendations than its users are able to obtain elsewhere? Time will tell, but that's not the big question. The big question: are Nara and services like it really solutions looking for problems?
While there is no doubt great opportunity in discovery at the local business level, a skeptic might suggest that finding a great restaurant, hotel or entertainment venue isn't all that difficult today thanks to reviews websites like Yelp. They are often the first places consumers turn when they're looking to discover local businesses, and in some cases, reviews can make or break a consumer's decision to give a business a chance.
With this in mind, Nara's biggest challenge may be convincing consumers that its neural network can better predict whether they'll like a particular business than human reviews of that business. If that proves to be the case, Nara may have its work cut out for it.
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