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November 19, 2007
Natural Language and the Semantic Web: ISWC Keynote talk
I gave an invited keynote talk last week at The 6th International Semantic Web Conference and the 2nd Asian Semantic Web Conference, 2007. The abstract for the talk is below. The image below links to the original video and presentation slides.
The live presentation (and video) contains technical demos that aren't in the slides. Some of the demos are already available inside Powerlabs (e.g. Powermouse, which lets you browse and query our semantic database of facts extracted from Wikipedia), while some of these are still internal (e.g. an open search box, and output of our natural language system on full sentences). I also gave some detailed walk-through showing how Powerset takes advantage of external semantic resources like Wordnet and Freebase.
For me, the most fun part of the talk was toward the end, where I got to speculate on how ecosystem effects can make natural language search and the semantic web become deeper and more powerful more quickly than people might expect. For example, advertisers, publishers, and vertical search sites will be able to contribute ontologies that enable them to get more users, better internal search, and more revenue, while having as a side effect that the broad search engines get more knowledgeable about different domains. The questions afterward were also challenging and interesting.
POWERSET - Natural Language and the Semantic Web
The Semantic Web promises to revolutionize access to information by adding machine-readable semantic information to content which is normally interpretable only by people. In addition, it will also revolutionize access to services by adding semantic information to create machine-readable service descriptions. This ambitious vision has been slow to take off because of a chickenand egg problem. Markup is required before people will build applications, applications are required before it is worth the hard work of doing markup. Natural language processing (NLP) has advanced to the point where it can break the impasse and open up the possibilities of the Semantic Web. First, NLP systems can now automatically create annotations from unstructured text. This provides the data that semantic web applications require. Second, NLP systems are themselves consumers of semantic web information and thus provide economic motivation for people to create and maintain such information. For example, a new generation of natural language search systems, as illustrated by Powerset, can take advantage of semantic web markup and ontologies to augment their interpretation of underlying textual content. They can also expose semantic web services directly in response to natural language queries.
Posted by barney at November 19, 2007 8:29 PM
This entry was posted in the following categories: Collective Intelligence , Human Language Technology , Powerset , Search
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