text mining – Ixa Group. Language Technology. https://www.ehu.eus/ehusfera/ixa News from the Ixa Group in the University of the Basque Country Wed, 13 Apr 2011 08:37:19 +0000 en-US hourly 1 https://wordpress.org/?v=5.6.4 Roser Morante’s talk: Modality and negation in natural language processing (2011/02/23) https://www.ehu.eus/ehusfera/ixa/2011/02/15/roser-morantes-talk-modality-and-negation-in-natural-language-processing-20110223/ https://www.ehu.eus/ehusfera/ixa/2011/02/15/roser-morantes-talk-modality-and-negation-in-natural-language-processing-20110223/#comments Tue, 15 Feb 2011 12:42:59 +0000 http://www.ehu.eus/ehusfera/ixa/?p=239

current trends and future directions Summary: Research on modality and negation focuses on [...]]]> Speaker: Roser Morante Senior researcher on the BIOGRAPH project led by Walter Daelemans.  CLiPS-Computational Linguistics research group University of Antwerp, Date: February 23, 2010 Time: 16:00 Where: Computer Science Faculty, Meeting room (batzar aretoa) .

Modality and negation in natural language processing: 

current trends and future directions

Summary:
Research on modality and negation focuses on finding subjective,
uncertain and counterfactual information in texts, be it in scientific
papers, product reviews, or opinions in blogs. This type of +research is
concerned with processing texts at the information level and aims at
deep text understanding.  Modality and negation are phenomena relevant
for all applications that are concerned with +some form of text
understanding, including text mining, sentiment analysis, recognizing
textual entailment, information extraction, text summarization, and
question answering. Hence, the adequate +modeling of these phenomena is
of crucial importance to the natural language processing (NLP) community
as a whole.

Whereas from a theoretical perspective, the study of modality has a long
tradition, only in the recent years have these topics attracted the
attention of NLP researchers. Mainly, the development of +sentiment
analysis techniques and the growing need of mining biomedical texts have
been the causes for the interest in these semantic aspects of language.
In this talk I will define modality and +negation from an NLP
perspective, I will motivate the need for processing these phenomena,
and I will summarize existing research on processing modality and
negation, touching on diverse aspects +ranging from task modelling to
feature visualization. Finally, I will speculate about future
developments in this research area.
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Wauter Bosma: Contextual salience in query-based summarization (2010/10/22) https://www.ehu.eus/ehusfera/ixa/2010/10/15/wauter-bosma-contextual-salience-in-query-based-summarization-20101022/ https://www.ehu.eus/ehusfera/ixa/2010/10/15/wauter-bosma-contextual-salience-in-query-based-summarization-20101022/#respond Fri, 15 Oct 2010 22:19:21 +0000 http://www.ehu.eus/ehusfera/ixa/2011/01/20/wauter-bosma-contextual-salience-in-query-based-summarization-20101022/ Speaker: Wauter Bosma (Vrieje Universiteit Amsterdam) Date: Oct 22, 2010 Time: 15:00 Where: Computer Science Faculty, room 2.2 .

Wauter Bosma is currently working as a postdoc on the European KYOTO project (where Ixa group is another partner) at the Vrieje Universiteit Amsterdam . His main research interests are in the area of Natural Language [...]]]> Speaker: Wauter Bosma (Vrieje Universiteit Amsterdam)
Date: Oct 22, 2010
Time: 15:00
Where: Computer Science Faculty, room 2.2 .

Wauter Bosma is currently working as a postdoc on the European KYOTO project (where Ixa group is another partner) at the Vrieje Universiteit Amsterdam . His main research interests are in the area of Natural Language Processing, and in particular text mining, terminology extraction and automatic summarization. In 2008 he received his PhD from the University of Twente on ‘Discourse-oriented summarization’.

Discourse theories claim that text gets meaning in context. Most summarization systems do not take advantage of this. They assess the relevance of each passage individually rather than modeling the way context affects the relevance of passages. In order to model relations in text, I developed a framework for graph-based summarization, so that the passages can be viewed in a broader context. The result is a summarization system which is more in line with discourse theory but still fully automatic. I evaluated the content selection performance of an implementation of the framework in different configurations. The system significantly outperforms a competitive baseline (and participant systems) on the DUC 2005 evaluation set.

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