Jennifer Zaino
SemanticWeb.com Contributor

His company, startup Peer39, uses proprietary semantic technology to help advertisers and publishers more closely match ads to web page content, based on being able to understand the meaning of the content on the page, including its sentiment (whether it's a positive or negative citation about a company, for example).

Solomon defines Web 3.0 like this: Whereas Web 1.0 was all about the excitement of just being able to create a static site, Web 2.0 brought interactivity to the picture. Web 3.0 is about taking the information that's out there, creating algorithms so that machines can understand what that content actually means, and then use that knowledge to monetize that content.

What makes that so special to advertisers in these fiscally challenged times? In an interview, Solomon began by pointing out a personal example. When his company was recognized by MIT as one of the top startups to watch in an article that discussed the technology in the context of emerging trends like social networks, there was, within that article, an insertion ad for Intel. Clearly, though, the ad was related to the vendor and computer networking technology, not social networks.

"So Intel spent a lot of money on that one keyword, 'networks,'" says Solomon, but the ad's appearance in the context of that story wasn't likely to generate the click-throughs Intel would have like to see, because the audience reading that piece was interested in social networks. "There are billions of those on the Internet on every page. The same mistakes. When you don't understand the content of things you miss again on the context of stuff."

In a down economy, advertisers are thinking hard about how to spend their budgets more wisely. "There's a big shift of dollars moving into better targeting, and semantics will definitely play in that category, based on what we are seeing," says Solomon. "It's a well-known fact that every network and advertiser wants more targeted ads now. Everyone."

Solomon says his company expects a very strong quarter in Q4 and next quarter, thanks to this trend and in spite of the economy.

He also expects that Peer39's ability to let publishers get more inventory out of their existing content is going to play well in tough times. Here's why: Take, for example, an article a newspaper web site categorizes as 'politics' because it's about a comment Presidential candidate Barack Obama made on green technology. Politics is hot as an identifier for ad impressions and can sell well over the next few weeks. But once the election is over, interest may drift, and an article that the publisher characterized as being about politics may be harder to sell ads against. But because that content is also about green technology, and probably also about alternative energy -- topics that may continue to stay fresh even as the election hoopla fades -- a publisher can get more life out of the article in terms of ad impressions, if it uses a technology like Peer39's, Solomon says.

"There may be a lot of companies that want to target based on those categories, so we are able to target to that page even if it was not manually characterized that way." That's because Peer39 mimics what humans do-identify multiple themes in an article-and translate that to a machine readable, automated, and scalable process.

"Big content players are looking to diversify their offerings and have more inventory available based on advertising needs," he says.

Solomon thinks 2009 will also be a year where more government focus will be on cookies and on having companies ensure they give users the right to opt out of leaving trails. Even in the absence of government intervention, he says more companies, depending on the industry they're in, are concerned about sites' use of cookies, even as they want to target ads to specific audiences. From that perspective, he thinks Peer39 will also be able to take advantage of the Web 3.0 monetization trend by attracting the business of companies and ad agencies looking for targeted solutions that don't use cookies.

"Semantic technologies understand the meaning of a page vs. random keywords, and we don't need cookies that have privacy issues to do it," he says.