Muntsa Padro

Muntsa Padro
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Main area of research
Natural language & AI

Muntsa is a Research Engineer in the NLU group. Her research interest is in the area of Natural Language Processing (NLP).

Muntsa graduated in Physics at the Universitat de Barcelona (Barcelona, Spain) in July 2002 and got her PhD on computer science at Universitat Politècnica de Catalunya on 2008. Her PhD thesis focused on the application of an automata learning algorithm to NLP tasks such as Named Entity Recognition, chunking and medical terminology detection. During and after her PhD she worked as a research assistant on the NLP group collaborating with FreeLing open source project and developing several NLP tools such as a HMM PoS tagger, a language identifier and a NER system based on AdaBoost among others.

From 2010 to 2013 Muntsa worked as a researcher at Universitat Pompeu Fabra for Panacea project. Muntsa’s work in the project was mainly devoted to perform research and development of tools for automatic lexical classification, subcategorization frame acquisition and merging of lexical resources. From April 2012 to August 2014 she did a PostDoc at Universidade Federal do Rio Grande do Sul (Porto Alegre, Brazil) working mainly on distributional semantics and semantic similarity induction.

Selected articles

Size does not matter. Frequency does. A study of features for measuring lexical complexity

Lexical simplification aims at substituting complex words by simpler synonyms or semantically close words. A first step to perform such task is to decide which

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Nothing like good old frequency: studying context filters for distributional thesauri

Much attention has been given to the impact of informativeness and similarity measures on distributional thesauri. We investigate the effects of context filters on thesaurus

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Comparing similarity measures for distributional thesauri

Distributional thesauri have been applied for a variety of tasks involving semantic relatedness. In this paper, we investigate the impact of three parameters: similarity measures,

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Finding dependency parsing limits over a large Spanish corpus

This paper studies the performance of different parsers over a large Spanish tree-bank. The aim of this work is to assess the limitations of state-of-the-art

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Verb SCF extraction for Spanish with dependency parsing

In this paper we present the results of our experiments in automatic production of verb sub-categorization frame lexica for Spanish. The work was carried out

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