|Fernando Pereira is research director at Google. His previous appointments include chair of the Computer and Information Science department at the University of Pennsylvania, head of the Machine Learning and Information Retrieval department at AT&T Labs, and research and management positions at SRI International. He received a Ph.D. in Artificial Intelligence from the University of Edinburgh in 1982, and he has over 120 research publications on natural language processing, machine learning, speech recognition, bioinformatics, databases, and logic programming as well as several patents. He was elected Fellow of the American Association for Artificial Intelligence in 1991 for his contributions to computational linguistics and logic programming, and he was president of the Association for Computational Linguistics in 1993.
|Addresses: www mail
- 15:15, Monday, July 19th, 2010
- Room FA1 - Pavilhão de Informática I (IST), 14:10
Information about the meanings of terms in context supports useful
inferences in a variety of language processing and information
retrieval tasks. We hypothesize that much of that information can be
derived from explicit and implicit relationships between terms in the
masses Web content and user interactions with that content. I will
describe initial tests of that hypothesis where we use graph label-
propagation methods to combine many small pieces of evidence from
unstructured and semi-structured Web text to bootstrap broad-coverage
instance-class relationships from a few seed examples.