Advertising platform C.A.S.T. wants to attract premium publishers interested in the concept of native advertising, and also interested in leveraging its possibilities through contextual and categorical targeting, among other means.

The company, which has been offering its advertising technology to its strategic partners for the last couple of years, now is bringing the platform to the broader medium- and large-size publisher market. “We see native advertising as advertising that integrates seamlessly as a very natural part of site-user behavior,” says Omer Kaplan, CEO and co-founder.

Today, native advertising is about helping publishers to have not only new but better-quality and more engaging inventory to sell to their advertisers, he says. With a native approach, ad units can be customized in terms of the placement and look of sponsored content that is related to what users are reading and what they are looking for – that is, designed with the semantics of the content in mind for a more natural flow between content and ads.

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ADmantX has released the findings of a new study “conducted on the top 10 US newspapers by simulating A/B testing using keyword targeting/semantic targeting on 20,000 pages from each publication. The analysis noted an average increase in ad reach up to 73% and an average increase in ad lift up to 48% using semantic targeting. Optimizing the match between content and ad is a fundamental step in making the economics of digital advertising work for buyer, seller and consumer.” Read more

Ryan Lawler of TechCrunch reports that semantic video technology company Affine has a new name: “Affine Systems first came to market several years ago with a product that helped advertisers deliver video ads with some pretty impressive brand safety features. Using a semantic video technology, Affine could scan videos frame-by-frame and group them together by relevance, enabling advertisers and agencies to build their own channels or content to run campaigns against. The only problem? No one could pronounce ‘Affine’.” Read more

If you would like your company to be considered for an interview please email editor[ at ]semanticweb[ dot ]com.

In this segment of our “Innovation Spotlight” we spoke with Elliot Turner (@eturner303), the founder and CEO of AlchemyAPI.com. AlchemyAPI’s cloud-based platform processes around 2.5 billion requests per month. Elliot describes how their API helps companies with sentiment analysis, entity extraction, linked data, text mining, and keyword extraction.

Sean: Hi Elliot, thanks for joining us, how did AlchemyAPI get started?

Elliot: AlchemyAPI was founded in 2005 and in the past seven years has become one of the most widely used semantic analysis APIs, processing billions of transactions monthly for customers across dozens of countries.

I am the Founder and CEO and a serial entrepreneur who comes from the information security space.  My previous company built and sold high-speed network security appliances. After it was acquired, I started AlchemyAPI to focus on the problem of understanding natural human language and written communications.

Sean: Can you describe how your API works? What does it allow your customers to accomplish?

Elliot: Customers submit content via a cloud-based API, and AlchemyAPI analyzes that information in real-time, transforming opaque blobs of text into structured data that can be used to drive a number of business functions. The service is capable of processing thousands of customer transactions every second, enabling our customers to perform large-scale text analysis and content analytics without significant capital investment.

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Who doesn’t love a targeted ad? Users prefer them, and content networks and supply-side advertising players are okay with them, too – that is, until they get a little too narrowly targeted. Why? While CPMs go up, the inventory volume is so low that less money gets made. On top of that, smarter targeting eats more CPU cycles in the data center, so it’s costing more money to make less.

That’s the picture Tim Musgrove, chief scientist at Federated Media Publishing, laid out for Semantic Tech & Business conference attendees at a session during the event yesterday. Then he explained how Federated Media’s Conversation Targeting semantic-powered ad targeting platform has changed things.

“It’s different for Federated Media because we have an entirely different way to approach this that avoids this decline of revenue that you see,” he said. That different way includes the tech of Conversation Targeting, of course, but also the business side of advertising negotiations.

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Q: What do Google, Microsoft, Yahoo!, Yandex, the New York Times, and The Walt Disney Company have in common?

A: schema.org

On June 2, 2011, schema.org was launched with little fanfare, but it quickly received a lot of attention. Now, almost exactly one year later, we have assembled a panel of experts from the organizations listed above to discuss what has happened since and what we have to look forward to as the vocabulary continues to grow and evolve, including up-to-the-minute news and announcements. The panel will take place at the upcoming Semantic Technology and Business Conference in San Francisco.

Moderated by Ivan Herman, the Semantic Web Activity Lead for the World Wide Web Consortium, the panel includes representatives from each of the core search engines involved in schema.org, and two of the largest early implementers: The New York Times and Disney. Among the topics we will discuss will be the value proposition of using schema.org markup, publishing techniques and syntaxes, vocabularies that have been mapped to schema.org, current tools and applications, existing implementations, and a look forward at what is planned and what is needed to encourage adoption and consumption.

Panelists:

	Moderator: Ivan Herman Semantic Web Activity Lead, World Wide Web Consortium		Dan Brickley Contractor, schema.org at Google
	John Giannandrea Director Engineering, Google		Peter Mika Senior Researcher, Yahoo!
	Alexander Shubin Product Manager, Head of Strategic Direction, Yandex		Mike Van Snellenberg Principal Program Manager, Microsoft/Bing
	Evan Sandhaus Semantic Technologist, New York Times Company		Jeffrey W. Preston SEO Manager, Disney Interactive Media Group

These panelists, along with the rest of the more than 120 speakers from SemTechBiz, will be on-hand to answer audience questions and discuss the latest work in Semantic Technologies. You can join the discussion by registering for SemTechBiz – San Francisco today (and save $200 off the onsite price)

Are you wondering why your product pages don’t stand out in search results like those from Amazon (shown below) or other competing e-commerce websites? These expanded results are commonly known as Rich Snippets (as named by Google) and are the result of having your HTML structured correctly with semantic markup. Whether you’re savvy to HTML5 and the latest design trends, or you haven’t updated your website code in years, this is article will explain why it’s important you structure your data properly utilizing semantic standards.

There are a number of ways to structure your data to make it more relevant to search engines, as well as social media sites. As an e-commerce retailer it is important to understand which of these standards you should consider including in your website. You should take some time to ensure you are implementing semantic markup, and doing it correctly. It has the power to better inform potential customers with upfront knowledge prior to landing on your site. Customers can see product reviews, pricing and stock information, and even images before clicking through to your website. This can lead to increased click-through rates, improve conversions, and generally enhance your SEO objectives.

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Searching on the web gets better with semantic technology. How about searching in your local supermarket?

Point Inside launched a private ad network offering this week that blends indoor shopper- and product-location technologies with proprietary semantic matching features to understand how what’s on users’ digital grocery lists can connect to what’s on a store’s shelves – and to opportunities to deliver in-context deals to consumers who opt in at the appropriate point in time.

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Late last week Bloomberg Businessweek reported that Facebook is working on an improved search engine with 20 developers under the direction of former Google engineer Lars Rasmussen, who joined the social network giant in 2010. According to the article’s unnamed sources, the goal “is to help users better sift through the volume of content that members create on the site, such as status updates, and the articles, videos, and other information across the Web that people ‘like’ using Facebook’s omnipresent thumbs-up button.”

As the news starts to make its way around the Web, the focus is on how this can intensify the competition between Facebook and Google, even if Facebook doesn’t directly go after the big web search enchilada. (Most seem to agree that it isn’t, at least not yet.) Better searching inside its own four walls, with its ability to use its host of knowledge about friends’ social graph data – their Likes and more – to more accurately personalize results, might encourage users to stay where they are rather than head out to search engine land, at least for some things. And at the same time let Facebook hone its advertising to profit from improved search results, too.

It would be an interesting turn of events, to have the leading search engine face the dilemma that online publishers long have been trying to deal with – keeping visitors engaged and exploring on their own sites rather than departing for Google in search of related information. As The Semantic Web Blog reported this week in a story about premium publishers deploying more semantic technology to try to solve that issue, most premium publishers lose 30 to 50 percent of their traffic to search engines.

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Once upon a time there was a semantic web startup dubbed Knewco, touting a knowledge discovery/ contextual advertising system for health care and life sciences content providers and advertisers (see this story). After a long journey toiling in the land of targeted health sites, it realized these prospects didn’t provide the best opportunity for its micro-targeted ad strategy. So, with a restructured management team and some fresh capital in place, in the latter half of 2011 it began a new quest: To become the semantic platform for premium publishers to help deliver personalized content recommendations and ads to readers and get more revenue, traffic and stickiness in the process.

Renamed Personalized Media, and now headed by CEO Rajiv Salimath, principal back in the Knewco days, the company’s technology now is in an advanced testing stage with premium publishers who will be white-labeling the system. Salimath can’t disclose their names, but suffice it to say that you’ve seen some of them prominently mentioned in these virtual pages before. So, what does Personalized Media bring to the party that’s attractive to some of these sites that already have taken steps – sometimes big ones – to bring semantic intelligence to their web presence?

From There to Here

When The Semantic Web Blog spoke with Salimath in late 2009, he discussed the technology’s prowess at understanding concepts and inter-relating them to other ideas. In its current incarnation, Personalized Media’s semantic search algorithms make it possible to find and suggest to readers other content – text, video, even apps, from the source itself, its associate properties or elsewhere on the web, depending on publisher preferences – that’s relevant to any word or term they highlight, or to the page at large. The content appears in a bubble at the user’s click.

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