Startup Helps Find What You Weren’t Looking for

Earlier this month, semantic startup SemantiNet announced that it had secured $3.4 million in Series A funding from Israel’s leading venture capital fund, Giza Venture Capital, as well as several private investors. Today, it unveils the first fruits of those efforts.

So, what’s all the buzz about? The browser plug-in, which initially will work with Firefox with an Internet Explorer version due shortly, is designed to help people discover content they are not actively searching for, founder Tal Keinan said. The company has taken advantage of APIs to access the content of sites with appeal to the social Web and digital lifestyle crowd, such as Wikipedia, Facebook, Twitter, YouTube, FlickR, and Amazon, encapsulating the source’s data with a semantic layer that describes the information each source provides.

For instance, Amazon provides information about products, and the characteristics of products are price, pictures, ratings, reviews, and reviews are written by people on certain dates. With Facebook, the semantic layer can encapsulate information such as a person’s name, location, birth date, friends’ list, interests, and such.

Once the product identifies objects on a page, and a user interacts with it, SemantiNet goes ahead and retrieves all the relevant content around that object, taking into account user interests, tastes, relationships, and so forth.

SemantiNet’s proprietary engine understands how the different pieces of information connect together and automatically creates those connections — contextually driven dynamic mash-ups, if you will. For instance, say you’re looking at a profile page on Facebook of a friend, and it indicates he’s a fan of a particular band; clicking on the band will bring up a bunch of information from the Web such as videos, songs, concert dates, and even who you know who might be going to what concert on what date.
Keinan said he had that experience himself, and saw through the Twitter connection that someone who he was friends with on Facebook but not on Twitter was attending the same concert he was going to on the same day. “I wouldn’t have known that otherwise,” he says.

That gets to the heart of what Keinan sees as a problem that has grown along with the Web.

“We are reaching a point where there is so much information contained in different sites and the level of noise surging around those sources. People understand that there needs to be some change in the way people consume content,” he said.

Some of what SemantiNet aims at doing sounds familiar, and Keinan says he gets the most questions about how it compares to AdaptiveBlue.

“The main difference is that what AdaptiveBlue does — it recognizes objects on pages, which is similar to us,” he says, but lacks the granularity of connections SemantiNet offers. “Our product knows that Coldplay, for instance, is a band, who are its members, the albums and songs, and takes advantage of all these pieces when it brings in information and reasons on them. So when I look at Coldplay I discover five of my friends are fans or going to concerts where I am. With AdaptiveBlue, you can search for Coldplay videos on YouTube, but you don’t understand how it is related to your world.”

Keinan says SemantiNet also offers an entirely different experience from TWINE.

“That’s also obviously a semantic product, but I view it as del.i.cious on steroids. You can share content with friends there and then go to TWINE to see how different pieces of content is correlated. We are different. We understand our users. You tell us what you do, which IDs you have on other sites, and we learn who you are based on that information that exists about you.

It retrieves information about your interests and friends, and as you browse it brings in these pieces and enhances the pages you view. You can go to YouTube and even if not a YouTube member we can tell you five of your friends recently uploaded new videos or here are videos that match your interests.”

SemantiNet says it decided to provide the technology as a client product in order to address any concerns about privacy, as well as data volume and scalability. It stores the information about who you are on your own hard drive, and issues content requests from there to the data provider rather than through SemantiNet’s own servers.

SemantiNet has not yet settled on which strategy it will use to generate revenue out of its technology, but he does say they don’t plan to leverage affiliate commissions as a business model. But Keinan sees possibilities even in enterprise usage, and says SemantiNet is in discussions about pilots around that.

“The Internet is the most complex system of all, an Internet of data sources that are completely dispersed,” he said. “If we can do that, we can go to the enterprise and say we’ve solved the Internet problem, we can now solve your problem integrating different products and data within the enterprise and connecting them with outside information.”

Article courtesy of Semantic Web

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