As you should know by now, we provide Web 2.0 developer tools and server product lines. Specifically, we provide Mashup products and technologies which enable the semantic extraction, aggregation, and use of remote web site content.

You probably are asking: "Semantic"... why the qualifier?

Because we've augmented the underlying "HTML scraping" capability with various pieces of knowledge about the HTML and the data contained within the HTML. The sum of which provides semantic knowledge.

Our approach to page analysis is fundamentally different from the traditional Semantic Web. Why? Because the traditional Semantic Web approach to understanding web content is to require the page author to annotate the page with meta data and/or apply AI techniques such as machine learning to determine content relevance/knowledge.

Both approaches are unlikely to succeed. Others have discussed the failure of these approaches and consequently either dismissed the Semantic Web vision in whole or dramatically limited the vision to user data from social sites and "facts" from online sites such as Wikipedia.

[Begin 09 April 2008 Update]

Tim Berners-Lee suggested this correction:

"...The basic Semantic Web approach is to surface data which is already in data-oriented applications and relational databases using standards.  it is not page annotation or machine learning! ..."

His comments and my response are below.

[End 09 April 2008 Update]

In this series on the Semantic Web, I will write about how we have built a modern and pragmatic implementation of the Semantic Web which is both faithful to the vision and achieves substantially more benefits to web users than previous designs or implementations.