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Posts Tagged ‘search-engines’

Local business search startup Localeze just announced that they will power some of Microsoft Bing’s local business listings. Microsoft will use Localeze’s 14 million listings for Bing Local and Bing 411.

As part of the deal, Bing will use Localeze’s premium business content, including more than 500,000 business-verified and managed listings, which have been edited directly by local businesses. In addition to name/address and contact info, Localeze’s listings also include hours of operation, products and services offered, credit cards accepted and more. All of this information will appear on Bing’s local business profiles. Any local search results on Bing utilizing Localeze content will be attributed to Localeze.

Bing seems to be building up its local listings to compete with Google’s vast database of local listings. Localeze promises keyword rich, verified and current local business content to local online search directories, vertical local search engines, social networking search sites, mobile search applications and Internet Yellow Pages. The company competes with InfoUSA and Acxiom.

The local listing space is getting hot. Earlier today, AT&T announced the launch of its own local listings site, Buzz.

Ginipic has partnered with Picitup to launch SpiderPic. That’s a lot of pics, and it will undoubtedly be not much of a surprise if I tell you the product has something to do with pictures. Stock photography, to be more specifpic specific.

SpiderPic is essentially a meta-search tool for stock photos that aggregates relevant shots from a host of third-party providers and lists results in one crisp interface, pricing from all (eight) suppliers included.

As pointed out on the Examples page, these price differences can be quite huge even for identical imagery, so if you find yourself regularly buying stock photos, this is a service you might consider bookmarking right now.

When you do a search for say, tablet, SpiderPic returns as much information as possible about each photo, and refer potential buyers to the source for actual purchases of photos or to get more detailed information such as promotions, special offers, and specific license restrictions.

The only thing that bugs me is that the prices or price range aren’t actually displayed when you get the list of search results, which means you have to click through every time.

Ginipic / Spiderpic co-founder Lior Weinstein tells me:

The technical challenge behind SpiderPic’s comparison feature, was to create a system that you can use only an image, with no text as a reference, and search in real-time between millions of images and return results within split seconds. We decided to partner with Picitup to supply the image recognition technology since they are by far the best out there – they serve top tier players such as eBay and Shopping.com.

SpiderPic also offers browser extensions to enable people to search and compare prices quickly from whatever browser they’re using (though the Google Chrome extension is still in the works).

SpiderPic plans on rolling out a similar image search feature soon, which will enable buyers to take any image they found on the web and find out whether the same or a similar image one is available for purchase for commercial purposes on the various agencies they support (Fotolia, iStockPhoto, BigStockPhoto, etc.). With the tool, the startup intends to make it possible for buyers to use any service on the web for searching images, without the need to worry about copyright infringement.

Weinstein admitted to me that the agencies are not all happy about the service, understandably. He says he has even received e-mails from some demanding that he remove their search results from SpiderPic. He doesn’t seem all too worried about it, though, and says that the same thing happened when the first regular online retail comparison shopping engines started popping up several years ago.

You can read up on Ginipic, which is a desktop application for searching images across photo sharing services, in my earlier review of the product.

There are so many music search engines out there based on YouTube music videos (Songza comes to mind) that it was only a matter of time until YouTube created its own music playlist maker. The YouTube Music Discovery Project just launched quietly out of TestTube (YouTube’s labs). The page is a search box on top of which says, “Find>Mix>Watch,” and once you enter a name, you hit the “Disco” button to find music.

You can enter any music group or artist, and a playlist pops up, along with a thumbnail video and a description of the band. You can find related artists, create a mixtape, and save playlists. As you are listening to music and watching videos, it is easy to add and delete songs.

YouTube is taking advantage of a lot of the officially-sanctioned Vevo music videos in the Music Discovery Project. Playlists are saved to your regular YouTube playlists page, from where you can share them via email. For instance, here is a playlist I crated called “Too Cool For School.” Oddly, there doesn’t seem to be any to purchase the music other than the occasional iTunes ad within the videos themselves. But this is an experimental product

(Hat Tip to Ron Ilan).

At today’s Real-Time CrunchUp, Mozzler launched its real-time search engine based on Twitter. Mozzler, which has real-time functionality, searches Twitter for the most popular content in the last six hours based on retweets.

You can search Mozzler by keyword, similar to searches you can do on OneRiot and other search engines that include Twitter results. Results can include videos and images as well. Mozzler has also created numerous categories of searches under technology, entertainment, sports, business and more.

What differentiates Mozzler is the ability filter the stream. You’ll be able to create customized streams by keyword, which are updated in real-time. You can share links to streams on social networks and users can also subscribe to streams.

And one particularly compelling feature is Track (which should be sure to make TechCrunchIT editor Steve Gillmor happy), which is like Google Alerts for Twitter. Twitter has yet to implement Track yet, but it’s a very desirable feature to help filter and “keep track” of the stream.

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MojoPages, a local listings search engine, has raised $5 million in Series A funding led by Austin Ventures. MojoPages’s search technology powers local business listing search engines for local newspapers, and TV and radio stations.

Originally a stand alone search engine for business listings, the company found that it could not compete with bigger players like Citysearch and Yelp. So Jon Gardner, CEO of MojoPages, decided to overhaul the site’s business model and offer white label, branded local search engine technology to media companies. The site’s listings are similar to Yelp in that they offer user reviews and ratings of businesses. To date, MojoPages has contracted with more than 1,000 media sites to create branded local business search engines.

Gardner says MojoPages will use the funds to expand the capabilities of its Yelp-like search engine, so that the search engine will become an aggregator of listings and reviews. The site hopes to pull local info from sites like Yelp, CitySearch, and YellowPages into one engine.

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A couple weeks ago, we wrote a post detailing why there needs to be some sort of iPhone app recommendation system. Just like iTunes has its “Genius” feature for music and movies, with over 50,000 apps now in the App Store, there needs to be a way to filter out what you don’t want and find what you do. If you have a lot of friends with iPhones or iPod touches, AppsFire may offer just that.

The service, launching in private beta today, allows you to share your favorite apps with anyone. Now, to be clear, I don’t mean actually share the apps themselves, but rather share the names of the ones you like and give others one-click access to download them also, from the App Store. So, say I have 100 apps on my machine, but I only really would recommend 15 or so, I would select those 15, and could send them out to friends on the various social networks.

AppsFire is actually an application that you install on you machine. Right now, it only works on Macs, but it’s coming for PCs soon. And there will event be an iPhone app, we’re told. Once the software is on your machine, it scans your iTunes folder to find your apps. It then opens a personal webpage on the AppsFire site and places the icons for your apps in front of you, asking you to choose your favorites. Once you do that, you can share them using the social networks, via email, in a widget, or simply get a link back to your AppsFire page. For example, here’s the link a co-founder of AppsFire, Ouriel Ohayon’s page.

It’s hardly a perfect system. First of all, the sharing mechanisms are a little clunky. And this isn’t a way to get personally tailored app recommendations based on what apps you already have an like. But it is a way to potentially find some new and interesting applications based on what people you know enjoy using.

The model for this is straight-forward: Affiliate links (through LinkShare and Tradedoubler), though Ohayon promises a “surprise” in that regard soon.

The limited private beta will be open to about 1,000 users at first, we’re told. You can sign up here.

Disclosure: AppsFire co-founder Ouriel Ohayon is a former member of the TechCrunch family, and still contributes from time to time.

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If you think you’re ready for some “moderate outrage,” strap in.

Go here to see the original: 
Fortune’s Stanley Bing ‘moderately outraged’ about Microsoft Bing

After hearing Brad Paisley say that a Fender Telecaster “is nothing more than a cutting board, a baseball bat, and strings,” Zachary Custom Guitars decided to put that idea to the test — minus the part about the baseball bat. The result: a guitar body made from a $25 butcher block from Ikea.

View original here: 
Weekend Project: Build an electric guitar from an IKEA cutting board

New search engine Topsy, which has been in stealth development for three years, launches, well, now.

Before Google, search engines like AltaVista determined relevance based on how well a web page matched the query. Then came Google, which views the web as a network of documents. Today, all search engines analyze linking behavior around the web. When a web page is linked to a lot, it’s given more influence than other pages competing for attention around the same topics/keywords. Jeff Jarvis summed it all up nicely in 2005 “In this new world, links are currency. Links grant authority. Links build branding. Links equal value.” There’s lots more to it, but the notion that links create value is what drives Internet search.

Well, it’s no longer 2005. Back then blogs were giving Google fits because of how fast and irregularly they updated. Google had to make decisions on how often to index pages. Indexing is expensive, so there’s a tradeoff. Ping servers and blog search engines rose briefly to fill the niche, but Google indexes most popular blogs so often that those blog search engines are no longer much better.

Now, though, we have so much real time content being created that Google and the other engines can’t keep up. Most of this content is on Twitter, but FriendFeed, Facebook, Digg and lots of other services are adding to it, too. The result - more and more people are doing searches on Twitter Search in addition to Google. For me, someone who’s obsessed with news and stuff that’s happening right now, Twitter search is about 25% of my total Internet searches. The ratio keeps going up over time.

That’s where Topsy comes in. It’s not strictly speaking a real time search engine like Scoopler, which we wrote about earlier this month. Topsy is just a search engine. That has a fundamentally new way of finding good results: Twitter users.

The 30 million or so Twitter users are an army of little content-finding machines. Topsy says those users are sending tens of thousands of unique links per day to interesting things around the Internet.

Some of those users have more influence than others. And some links are sent by lots of Twitter users, others just sent once. Those links, combined with the information in the Twitter message itself, is what Topsy uses as the basis of its search engine.

And the results are…amazing.

New stuff in particular percolates up very quickly. A search for Facebook, for example, shows lots of news about the funding that was announced earlier today. And the links are sorted by those that Twitter users are sending around the most, weighted in favor of links sent by more influential Twitter users. You can sort results over all time (going back to September 2008), last month, week, day or hour. For all time, top results for Facebook are the Facebook site and developer site, among others. But in the last hour and day, it’s all about the funding news.

Results show popular links but also the most influential users tweeting about that topic. Click on that user and you’ll see all their tweets about the topic. Here’s the results for TechCrunch and Facebook, for example.

User influence is a hot topic, of course. Topsy isn’t looking at the number of followers. Rather, Influence is gained when others retweet links you’ve sent out. And when you retweet others, you lose a little Influence. So the more people retweet you, the more Influence you gain. So, yes, retweets are the new currency on the web. Told you.

Topsy was founded in 2006 and has raised nearly $15 million to date in venture and debt funding. More information on the funding and founders is on the CrunchBase page for Topsy.

Here’s a video where the Topsy founders give an introduction to the service and how it works:

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Regular search engines such as Google and Yahoo use statistics to make sense of the Web. They count links, keywords, and other items on a page to determine its rank in search results. Semantic search engines try to actually understand the meaning of the words found on the Web and other documents to bring back the most relevant results to a query. Microsoft bought Powerset for $100 million to gain semantic search expertise, but so far all it can search is Wikipedia.. Hakia, Textwise, and other startups are also working on semantic search. Now comes NetBase, which brings a slightly different approach that its says can scale to the entire Web.

NetBase has been around for a while. Originally called Accelovation, it has raised $9 million in two rounds of venture funding over the past four years, has 30 employees, and counts among its current customers P&G, Caterpillar, 3M, BP, Kraft, BASF, and Goodyear. It is now changing its name and offering its core semantic indexing technology as a platform for other companies to build their own products. Already, scientific publisher Elsevier uses NetBase to power its Illumin8 research tool for searching scientific articles, patents, and Websites.

NetBase takes a sophisticated linguistic approach, actually diagramming sentences to determine the relationship between words and phrases. It does particularly well with causal relationships, allowing it to tease out cause and effect from raw text. For instance, in the sentence, “The calcium, potassium and magnesium found in yogurt can help reduce your risk for hypertension often resulting from stress, obesity, and other factors” NetBase can identify that “stress” and “obesity” are causes of hypertension and that “calcium,” “potassium,” “magnesium,” and “yogurt” can be used to counter hypertension.

The company has already indexed about 8 billion Web pages and processes 100 billion sentences a month through its semantic parsing. Once it identifies causes, effects, and other relationships, it can serve them up in search results along with top-ranked links. For instance, a health-related search could turn up a guide that includes related symptoms, causes, drugs, and treatments. The technology also lends itself to Q&A types of searches. You could ask, “What companies are developing semantic search technologies?” and it will return a list of companies along with the snippets of mention that company and semantic search.

I’ve tried a few demo searches set up to do various things such as provide the pros and cons of a product, the companies in a particular market, or causes and effects of a medical problem. The results were impressive. On the whole, I’d say they were at least 70 percent relevant, compared to the much larger proportion of irrelevant links I get when I do a Google search. But it was slow. NetBase took 5 seconds or more to return results, something it says won’t be as big an issue in a production versions of its technology.

NetBase is not building its own search engine, although it plans to create a health-related search engine around PubMed content as a proof of concept Instead, it is targeting large publishers and companies that want to create their won vertical search tools, which combine data on the Web with their own databases of content. This is definitely an enterprise play. Licensing starts at about $100,000 and goes up from there.

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