Natural Language Processing is very important to the Semantic Web. Language processing algorithm development will rise as better and smarter NLP agents are used to scour silos of raw textual data for semantic meaning. The addition of NLP Web services to the Web will give light to new and innovative mashups. An example mashup powered could be a service that uses a language processing agent to read a news article about the Apple iPhone and:

Continue reading Future value paradigms of the Semantic Web

Swoogle describes itself as being the search engine for the Semantic Web. Swoogle crawls the web looking for RDF documents. At this time Swoogle offers the these services:

• Search ontologies and instance data
• Search terms (URIs that have been defined as classes and properties)
• Provide metadata of Semantic Web documents
• Support browsing the Semantic Web
• Archive different versions of Semantic Web documents

Continue reading Swoogle - the Semantic Web search engine

The journey from now to the Semantic Web is a long one. What we currently have on our hands with the current version of the Web are billions of documents totaling terabytes of data. This data is usually found within HTML pages comprised mainly of non-validating markup and very little, if any, meta data.

While there are billions of documents on the Web that contain no meta data whatsoever there is one shining star of hope: Natural Language Processing. NLP can be used to sift through the "garbage" data to extract coherent statements about the information held within.

Continue reading Natural Language Processing and the Semantic Web

Let's face it, Web documents in their current state are just about the worst way we exchange data. It usually comes in the form of HTML or XHTML, and rarely validates to any degree. In order to begin our approach towards Tim Berners-Lee's dream of the Semantic Web we must begin writing valid, semantic markup.

Continue reading Semantic markup gives Web documents meaning