no code implementations • WS 2019 • Camiel Colruyt, Orph{\'e}e De Clercq, V{\'e}ronique Hoste
The functions are tested against the judgment of a human evaluator and a comparison is made between sets of tokens and sets of syntactic heads.
no code implementations • SEMEVAL 2019 • Nina Bauwelinck, Gilles Jacobs, V{\'e}ronique Hoste, Els Lefever
This paper describes our contribution to the SemEval-2019 Task 5 on the detection of hate speech against immigrants and women in Twitter (hatEval).
no code implementations • CL 2018 • Cynthia Van Hee, Els Lefever, V{\'e}ronique Hoste
Although common sense and connotative knowledge come naturally to most people, computers still struggle to perform well on tasks for which such extratextual information is required.
no code implementations • WS 2018 • Gilles Jacobs, Els Lefever, V{\'e}ronique Hoste
This paper presents a dataset and supervised classification approach for economic event detection in English news articles.
no code implementations • SEMEVAL 2018 • Luna De Bruyne, Orph{\'e}e De Clercq, V{\'e}ronique Hoste
This paper presents an emotion classification system for English tweets, submitted for the SemEval shared task on Affect in Tweets, subtask 5: Detecting Emotions.
no code implementations • SEMEVAL 2018 • Cynthia Van Hee, Els Lefever, V{\'e}ronique Hoste
Our shared tasks received submissions from 43 teams for the binary classification Task A and from 31 teams for the multiclass Task B.
no code implementations • WS 2017 • Orph{\'e}e De Clercq, Els Lefever, Gilles Jacobs, Tijl Carpels, V{\'e}ronique Hoste
This paper presents an integrated ABSA pipeline for Dutch that has been developed and tested on qualitative user feedback coming from three domains: retail, banking and human resources.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3
no code implementations • COLING 2016 • Cynthia Van Hee, Els Lefever, V{\'e}ronique Hoste
Recognising and understanding irony is crucial for the improvement natural language processing tasks including sentiment analysis.
no code implementations • SEMEVAL 2016 • Maria Pontiki, Dimitris Galanis, Haris Papageorgiou, Ion Androutsopoulos, Man, Suresh har, Mohammad AL-Smadi, Mahmoud Al-Ayyoub, Yanyan Zhao, Bing Qin, Orph{\'e}e De Clercq, V{\'e}ronique Hoste, Marianna Apidianaki, Xavier Tannier, Natalia Loukachevitch, Evgeniy Kotelnikov, Nuria Bel, Salud Mar{\'\i}a Jim{\'e}nez-Zafra, G{\"u}l{\c{s}}en Eryi{\u{g}}it
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2
no code implementations • LREC 2016 • Els Lefever, V{\'e}ronique Hoste
Breaking news on economic events such as stock splits or mergers and acquisitions has been shown to have a substantial impact on the financial markets.
no code implementations • LREC 2016 • Orph{\'e}e De Clercq, V{\'e}ronique Hoste
The fine-grained task of automatically detecting all sentiment expressions within a given document and the aspects to which they refer is known as aspect-based sentiment analysis.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2
no code implementations • LREC 2016 • Cynthia Van Hee, Els Lefever, V{\'e}ronique Hoste
Handling figurative language like irony is currently a challenging task in natural language processing.
no code implementations • WS 2015 • V, Vincent eghinste, Tom Vanallemeersch, Frank Van Eynde, Geert Heyman, Sien Moens, Joris Pelemans, Patrick Wambacq, Iulianna Van der Lek - Ciudin, Arda Tezcan, Lieve Macken, V{\'e}ronique Hoste, Eva Geurts, Mieke Haesen
no code implementations • LREC 2014 • Orph{\'e}e De Clercq, Sarah Schulz, Bart Desmet, V{\'e}ronique Hoste
We focus on both the word and character level and find that we can improve the BLEU score with ca.
no code implementations • LREC 2014 • Els Lefever, Marjan Van de Kauter, V{\'e}ronique Hoste
In this research, we evaluate different approaches for the automatic extraction of hypernym relations from English and Dutch technical text.
no code implementations • LREC 2014 • Bart Desmet, V{\'e}ronique Hoste
The best relevance classification is achieved by using SVM with post length, lemma and character ngrams, resulting in an F-score of 85. 6{\%} (78. 7{\%} precision and 93. 8{\%} recall).
no code implementations • LREC 2012 • Martin Reynaert, Ineke Schuurman, V{\'e}ronique Hoste, Nelleke Oostdijk, Maarten van Gompel
In this paper we report on the experiences gained in the recent construction of the SoNaR corpus, a 500 MW reference corpus of contemporary, written Dutch.
no code implementations • LREC 2012 • Els Lefever, V{\'e}ronique Hoste, Martine De Cock
The input for the inter-language link detection system is a set of Dutch pages for a given ambiguous noun and the output of the system is a set of links to the corresponding pages in three target languages (viz.