There’s a nasty, and very personal, lawsuit in progress between Radar Networks and a jilted investor, Kate Paley (daughter of CBS icon William Paley). The defendants include founder Nova Spivack, the company that eventually acquired Radar Networks (Evri) as well as investors Steve Hall, Ross Levinsohn and Baris Kardogan.
The company, known by most through it’s product Twine, was once doing quite well from an outsider’s perspective, but the reality, according to the lawsuit, is that the company was scrambling for ways to stay in business by 2008. The way that the company raised new money, and the details around its eventual sale to Evri, are a warning to any startup – sometimes it’s better to just shut down a failed company and move on. → Read More
After shopping itself around to all the major search engines, Radar Networks finally found a buyer in another semantic search startup. Today, Evri is announcing that it will be acquiring Radar Networks, along with its core technical team and its main product, Twine. Rumors surfaced yesterday on ReadWriteWeb that Evri was being acquired, but that is not the case. Evri is the acquirer. → Read More
Yesterday, Bing released a surprisingly useful new feature around recipe search. If you search for “Chicken,” you can narrow the results down by “chicken recipes” and then a whole bunch of new filtering options appear down the left-hand column. You can further narrow results by recipe rating, cuisine (vegetarian, Spanish, Southwestern), convenience (quick/easy, family, entertaining), occasion (wedding, Valentine’s Day), main ingredient, course, or cooking method. Bing is big on guided search (showing relevant search categories to help narrow results), but this goes one step further towards semantic search (the ability to index and search the Web by different facets). Recipes are just the beginning, and it’s not just Bing. Google and a handful of startups, including Evri, Hakia, and Radar Networks, are hard at work on making semantic search a reality. The race is on to bring this type of semantic filtering for nearly every category of search across the Web.
In fact, Bing’s recipe search looks a hell of a lot like T2, the semantic search engine being developed in private by Radar Networks. The startup currently offers a semantic bookmarking application called Twine which is on autopilot, but T2 is much more ambitious. Not many people have seen T2, but CEO Nova Spivack once gave me a demo and I took a bunch of screenshots like the one above (there are also slides on the Web). When you search for “chicken” on T2, you can also narrow by difficulty level, meal, main ingredient, dietary option, cuisine, course, and so on. Recipes happens to be one of T2′s strong suits. It has perhaps the largest semantic indexes of recipes in the world with 300,000 recipes. But it is also building out its semantic search index for video games, movies, music, travel, health, sports, and other category verticals. → Read More
Extracting meaning from the Web is huge project that is very difficult to do at large scale. Keyword search only skims the surface of meaning locked in Web pages. Various semantic search technologies try to go deeper by adding structured data to web pages so that the Web can be treated more like a database. But adding semantic metadata to the Web is laborious and time-consuming. Just look at Twine. It’s approach so far has been to add semantic data only to the Web pages members save to the service.
While it appeared like Twine was finally getting some traction earlier this year, it’s fallen by the wayside. Traffic is way down (see chart below), partly because it is no longer buying traffic with ads and partly because of changes to the way Google indexes the site. Bottom line is that is that beyond a hardcore following of about 250,000, Twine does not have broad appeal.
But CEO Nova Spivack and his team at Twine have been busy working on something else entirely, to the point that the current Twine service is pretty much on autopilot. In the video after the jump, Spivack gives a sneak peak at what his team has been working on. Codenamed T2, it is complete departure from the navel-gazing approach of Twine 1.0. It is a big step towards creating a semantic search engine that might eventually scale across the Web—exactly the kind of swing for the fences type of idea we like to see at TechCrunch. → Read More
A year after launching its beta, Twine opened up today to the general public with a completely redesigned site. The relaunch got lots of coverage. Maybe you read some of it. Even if you did, you probably still don’t know what Twine does. Some semantic shit, right?
Exactly. Twine’s marketing department made the video above as a joke for their staff meeting today. (Warning: Turn the volume down, NSFW). I think that is the best explanation I’ve heard yet of what Twine does. → Read More
As the Web swells with more and more data, the predominant way of sifting through all of that data—keyword search—will one day break down in its ability to deliver the exact information we want at our fingertips. In fact, some argue that keyword search is already delivering diminishing returns—as the slide above by Nova Spivack implies. Spivack is the CEO and founder of semantic Web startup Radar Networks and is pushing his view that semantic search will help solve these problems. But anyone frustrated by the sense that it takes longer to find something on Google today than it did even a year ago knows there is some truth to his argument. “Keyword search is okay,” he says, “but if the information explosion continues we need something better.” Today, there are about 1.3 billion people on the Web, and more than 100 million active Websites. As more people pile on, the amount of information on the Web keeps growing exponentially to accommodate all those seekers, and they themselves feel compelled to put their own personal and social information onto the Web as well. At a certain point, with billions and billions of Web pages to sift through, keyword search just won’t cut it anymore. It’s a needle-in-the-haystack problem, with the haystacks just getting bigger and bigger every second. Spivack explains: Keyword search engines return haystacks, but what we really are looking for are the needles . The problem with keyword search such as Google’s approach is that only highly cited pages make it into the top results. You get a huge pile of results, but the page you want—the “needle” you are looking for—may not be highly cited by other pages and so it does not appear on the first page. This is because keyword search engines don’t understand your question, they just find pages that match the words in your question. So how do we get beyond keyword search and Google’s PageRank? There are many approaches being tried: social search, tagging, guided search, natural-language search, statistical methods, open search, semantic search, and (way out there) artificial intelligence. They all have their problems. Tags are too messy and inconsistent. Natural-language requires too much computing power, is difficult to scale, and doesn’t deal with structured data well. Semantic search is perhaps the most promising, but it essentially requires every single Webpage to be re-written. Spivack covered these issues during a presentation → Read More
Radar Networks, the not-so-secret stealth startup, is finally unveiling its site, dubbed Twine. Twine is targeted straight at groupware and knowledge-management apps that have mostly been confined to enterprise installations, and opening that up to a broader base of consumers. The startup has raised $5 million from Paul Allen, Peter Rip, Ron Conway in April, 2006, and has done work for DARPA. CEO Nova Spivack took me through a demo. On the surface, Twine is a place to organize information you find or create on the Web—bookmarks, notes, videos, photos,contacts, tasks. (A Web browser plug-in makes it easy to save stuff to your Twine wherever you may find it on the Web). You can also share that information with a private group or publicly. Once you ingest in all the information you want to organize, Twine applies a semantic analysis to it that creates tags for each document or video or photo. The tags match up to concepts that Twine’s algorithms associate with each piece of content, regardless of whether that concept is specifically mentioned in the Web page or other content being tagged. For example, you might bookmark this post and Twine would create tags for all the people mentioned in it (Nova Spivack, Paul Allen, Peter Rip, and Ron Conway). It would also create tags for the organizations related to the post, such as Radar Networks and DARPA, but also Paul Allen’s venture firm Vulcan Capital—even if Vulcan was never mentioned in the post. What Twine does is automatically generate smart tags and connect them together. There is also a social element. If you share a Twine with others, each piece of content that someone brings into that online space is associated with that person. So when you do a search, the results that come back are influenced not just by the tags, but also by who put the information into the Twine in the first place. “It’s the wisdom of crowds plus the wisdom of computers working together,” says Spivack. The more closely related that person is to you, the higher the relevance. At the same time, Twine is creating a very detailed profile of your interests which it hopes to run highly targeted ads against. Twine is putting structure onto all of this unstructured data that is out there by analyzing it and adding tags to it that are connected together. The network of links between → Read More
San Francisco, CA
