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Visualitza Recerca: articles, congressos, llibres per matèria "Natural Language Processing"

Ara mostrant els elements 1-13 de 13

A Hybrid approach for biomedical relation extraction using finite state automata and random forest-weighted fusion

Mavropoulos, Thanassis; Liparas, Dimitris; Symeonidis, Spyridon; Vrochidis, Stefanos; Kompatsiaris, Ioannis (Springer, 2017)

The automatic extraction of relations between medical entities found in related texts is considered to be a very important task, due to the multitude of applications that it can support, from question answering systems to ...
A semantic model of selective dissemination of information for digital libraries

Morales del Castillo, José Manuel, 1974-; Pedraza, Rafael; Ruiz Rodríguez, Antonio Ángel; Peis, Eduardo; Herrera-Viedma, Enrique (ALA American Library Association, 2010)

In this paper we present the theoretical and methodological/nfoundations for the development of a multi-agent/nSelective Dissemination of Information (SDI) service/nmodel that applies Semantic Web technologies for ...
Automatic detection of sexism in social media with a multilingual approach

Altin, Lutfiye Seda Mut; Saggion, Horacio (CEUR Workshop Proceedings, 2021)

This paper describes the participation of the LaSTUS/TALN team in the shared task EXIST: sEXism Identification in Social neTworks at IberLEF 2021. EXIST promotes the development of classification systems able to spot ...
Context-aware automatic text simplification

Sheang, Kim Cheng (CEUR Workshop Proceedings, 2019)

Text simplification is the process of transforming complex text into simple text while retaining its original meaning. Simplified text is easy to read and understand by different groups of people, especially children, ...
Convolutional neural network language models

Boleda, Gemma; Pham, Nghia The; Kruszewski, German (ACL (Association for Computational Linguistics), 2016)

Convolutional Neural Networks (CNNs) have shown to yield very strong results in several Computer Vision tasks. Their application to language has received much less attention, and it has mainly focused on static classification ...
Distributional semantics in use

Boleda, Gemma; Bernardi, Raffaella; Fernández, Raquel; Paperno, Denis (ACL (Association for Computational Linguistics), 2015)

In this position paper we argue that an adequate semantic model must account for language in use, taking into account how discourse context affects the meaning of words and larger linguistic units. Distributional semantic ...
Distributional vectors encode referential attributes

Boleda, Gemma; Gupta, Abhijeet; Baroni, Marco; Padó, Sebastian (ACL (Association for Computational Linguistics), 2015)

Distributional methods have proven to excel at capturing fuzzy, graded aspects of meaning (Italy is more similar to Spain than to Germany). In contrast, it is difficult to extract the values of more specific attributes of ...
LaSTUS/TALN at HAHA: Humor Analysis based on Human Annotation

Altin, Lutfiye Seda Mut; Bravo Serrano, Àlex, 1984-; Saggion, Horacio (CEUR Workshop Proceedings, 2019)

In this paper we describe the participation of LaSTUS/TALN team in the shared task:“Humor Analysis based on Human Annotation” (HAHA) at the Spanish Society for Natural Language Processing (SEPLN) organized in the context ...
LaSTUS/TALN at TASS 2019: sentiment analysis for spanish language variants with neural networks

Altin, Lutfiye Seda Mut; Bravo Serrano, Àlex, 1984-; Saggion, Horacio (CEUR Workshop Proceedings, 2019)

This paper describes the participation of LaSTUS/TALN team in the shared task Sentiment Analysis at SEPLN (TASS) organized in the context of IberLEF 2019. TASS focuses on the classification of tweets written in the Spanish ...
Living a discrete life in a continuous world: reference with distributed representations

Boleda, Gemma; Padó, Sebastian; Pham, Nghia The; Baroni, Marco (ACL (Association for Computational Linguistics), 2017)

Reference is the crucial property of language that allows us to connect linguistic expressions to the world. Modeling it requires handling both continuous and discrete aspects of meaning. Data-driven models excel at the ...
“Look, some green circles!”: learning to quantify from images

Boleda, Gemma; Sorodoc, Ionut-Teodor; Lazaridou, Angeliki; Herbelot, Aurélie; Pezzelle, Sandro; Bernardi, Raffaella (ACL (Association for Computational Linguistics), 2016)

In this paper, we investigate whether a neural network model can learn the meaning of natural language quantifiers (no,some and all) from their use in visual contexts. We show that memory networks perform well in this ...
“Show me the cup”: reference with continuous representations

Boleda, Gemma; Baroni, Marco; Padó, Sebastian (Springer, 2018)

One of the most basic functions of language is to refer to objects in a shared scene. Modeling reference with continuous representations is challenging because it requires individuation, i.e., tracking and distinguishing ...
The LAMBADA dataset: word prediction requiring a broad discourse context

Boleda, Gemma; Paperno, Denis; Kruszewski, German; Lazaridou, Angeliki; Pham, Quan Ngoc; Bernardi, Raffaella; Pezzelle, Sandro; Baroni, Marco; Fernandez, Raquel (ACL (Association for Computational Linguistics), 2016)

We introduce LAMBADA, a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative passages sharing the characteristic that ...