The basic premise of Cogito is that it transforms unstructured information into structured data. Out of this process comes a "semantic network", which is much the same thing as what rival company Cognition called a "semantic map" in our September '08 interview with them. It's important to point out that Cogito isn't necessarily a 'Semantic Web' application, but it does use things like natural language processing and other semantic analysis. It can output RDF, but that isn't a fundamental part of Cogito.

Brooke Aker described the system to us as being like an "electronic dictionary". There are 350,000 words and 2.8 million "relationships" in Cogito. Cognition claimed 10 million "semantic connections" in its map back in September, but Aker suggested that it wasn't quite an apples and oranges comparison. According to Aker, Cogito's semantic network is "richer" than Cognition's.

Expert System's new semantic advertising solution, Cogito Semantic Advertiser (CSA), came about because the company saw that traditional contextual keyword advertising is resulting in a lot of inaccuracies and mistakes when matching ads to page content. The classic example is the jaguar one, where a story about a jaguar (the animal) is accompanied by a 'contextual' advert for jaguar the car. Expert System told us that this kind of scenario won't occur with their semantic advertising system.

Expert System claims to have come up with an advertising solution that understands "the real meaning" of words, based on theories of human comprehension. For example, their system analyzes the semantic meaning of words and their context. So in the jaguar example, Expert System would 'understand' that jaguar is an animal in the context of the story - and therefore it would not serve up ads about the jaguar car.

One feature of Cogito Semantic Advertiser that stood out for us was the granular categorization, which allows for very fine grained targeting of ads. Brooke Aker told ReadWriteWeb that their product has already created around 2 million niches for advertisers to target, which is something that many Long Tail publishers will find appealing.

We're impressed by the semantic software that Expert System is producing, not just with advertising but in other commercial and government applications. Let us know in the comments if you've come across this company before and if so, what your thoughts are.

To fully appreciate how Web 3.0 can offer better advertising solutions, Solomon suggested that we start by analyzing the Web's transformations since Tim Berners-Lee and Robert Cailliau wrote the official proposal for the World Wide Web in 1990.

Web 1.0 was basic connection via the Internet, where information flowed one way and was rarely updated. Web 1.0 ended in 2001 with the crash of the dot com era that some estimate cost in excess of $5 Trillion. The Web 1.0 lesson: Cash, not content, is king.

Web 2.0 marked the beginning of the 'two sided Internet,' where we started using the Internet to talk to one another. This interactivity generated billions of dollars in data - virtually for free. The Web 2.0 lesson: Sustainable revenues are possible.

Web 3.0 offers detailed data exchange to every point on the Internet, a 'machine in the middle,' with three main characteristics:

1. Smart internetworking

The Internet itself will get smarter and become a gathering tool to execute relatively complex tasks and analyze collective online behavior.

2. Seamless applications

Web 3.0 theories suggest that all applications will fit together; a continuation of open source where all applications will be able to communicate. APIs will read data from any platform and provide a single point of reference.

3. Distributed databases

Web 3.0 will need somewhere to store very complex and memory intensive information. It will require ontologies to establish relationships between information sources; search millions of nodes, and scan billions of data records at once.

How Does This Make Money?

"This is where the semantic Web comes in," Solomon explained. "Businesses finally understand the Internet, and recognize that advertising is a good business model - if you can make it work."

According to Solomon, there are two approaches to advertising currently being used; contextual advertising and behavioral targeting:

Contextual advertising systems scan website text for keywords that trigger the system to send predetermined ads. Used in search engine results page, contextual systems show ads based on users search words; unfortunately, these ads aren't always relevant as words can have several meanings. While errors occasionally result in humor, and are good for a laugh, contextual ads show a serious weakness: companies investing in them are wasting advertising budgets, brand promotion and sentiment.

Behavioral targeting systems collect information on a person's Web browsing history, usually by way of cookies. Given the European Union's Directive 2002/58 on privacy and electronic communications, and pending US legislation restricting the use of cookies, behavioral targeting campaigns via cookies can no longer be seen as a valuable investment. Additionally, home computers are oftentimes shared, and if cookies are enabled, users get to see ads directed by other user's cookies. Again, badly targeted advertising can be a nuisance for the user, and a waste of advertising dollars.

The Way of the Future: Semantic Advertising

Successful advertising means showing the right product to the right person at the right time. The semantic Web puts data into semantic formats on the fly, and targets ads based on the meaning of data with a high degree of accuracy.

This is good news for the user - no more embarrassing keyword results, no more Hooters ads on sites about feminism, and an end to annoying cookies.

Do you agree that the Semantic Web will bring even more effective advertising to the Web?

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