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:
- Google Maps API: Provide a map of Apple store locations
- Amazon E-Commerce API: Display product information and a link
- Flickr API: Show pictures of the iPhone
An example of current-generation Natural Language Processing for the Semantic Web is ClearForest SWS. This service is a step in the right direction, and a preview of how NLP will be used in the Semantic Web to extract meaning from text. ClearForest SWS is still lacking in accuracy. For example, it might identify "McDonalds Big Mac" as business name, when "McDonalds" would have been correct.
The extensibility of RDF comes from the ability for anyone to create their own vocabulary, thereby extending RDF to describe any conceivable information set. As the Semantic Web grows and matures, thousands of new vocabularies will appear and many will merge, split, and overlap. By utilizing common vocabularies it is possible to increase the potential for interoperability among RDF applications.
More to write about
There is much more to cover and I will continue writing on this topic in the future.
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