Valeria de Paiva

Valeria de Paiva
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Main area of research
Natural language & AI

Valeria de Paiva is a Senior Research Scientist in the Artificial Intelligence and Reasoning group. Her research interest is in the area of Natural Language & AI. As a mathematician, logician and computer scientist, she uses logic to improve communication with computer systems. Before Nuance, she was a research scientist at the Intelligent Systems Laboratory of PARC (Palo Alto Research Center), CA for many years (2000-2008) and a search analyst at Cuil, Inc. and at Rearden Commerce, now Deem. She received her PhD in Mathematics from Cambridge University for work on “Dialectica Categories”, and has ever since worked on logical approaches to computation. She is on the editorial boards of “Theoria and Application of Categories”, “Logical Methods in Computer Science” and of “Logica Universalis”. She's an Honorary Research Fellow at the School of Computer Science, University of Birmingham, UK, where she was an Assistant Professor, and she taught recently at Stanford University and Santa Clara University in California.

Selected articles

As Wordnets do Português

Not many years ago it was usual to comment on the lack of an open lexical-semantic knowledge base, following the lines of Princeton WordNet, but

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Explaining Watson: Polymath Style

Our paper is actually two contributions in one. First, we argue that IBM’s Jeopardy! playing machine needs a formal semantics. We present several arguments as

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Exploratory Information Extraction from a Historical Dictionary

We describe a preliminary project of extracting information from an extant dictionary of historical biographies, the “Dicionario Historico-Biografico Brasileiro” (the Brazilian Historical and Biographical Dictionary,

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Linear Logic Model of State Revisited

In an unpublished note, Reddy introduced an extended intuitionistic linear calculus, called LLMS (for Linear Logic Model of State), to model state manipulation via the

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Ontologies in Enterprise Applications: Dimensional Comparison

Many important categories of applications such as information integration, data analytics, and personal assistance require access to a general store of knowledge. The usefulness of

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