Thomas Hofmann from Google Research gave a keynote lecture on how they are bringing semantics to the web. He explained how interesting models can be scaled to web size by using curated knowledge bases (eg Freebase) and the output from accurate but slower parsers as the either the starting point to statistical analysis or training data for faster systems.
Bran Boguraev from IBM's TJ Watson Research Center talked about evidence based reasoning over natural language content. The example was of course their massively parallel Watson architecture for large-scale hypothesis generation, validation and scoring which tackles the long-standing challenge in AI to emulate human expertise.
Hans Uszkoreit introduced the outline for META-NET's strategic research agenda for language technology in Europe. The vision paper presents possible futures for innovative language technology applications in the following areas:
- language-transparent web and media experience,
- natural and inclusive interaction, and
- efficient information management.
No comments:
Post a Comment