Marjan Van de Kauter


2017

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Noise or music? Investigating the usefulness of normalisation for robust sentiment analysis on social media data
Cynthia Van Hee | Marjan Van de Kauter | Orphée De Clercq | Els Lefever | Bart Desmet | Véronique Hoste
Traitement Automatique des Langues, Volume 58, Numéro 1 : Varia [Varia]

2015

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LT3: Applying Hybrid Terminology Extraction to Aspect-Based Sentiment Analysis
Orphée De Clercq | Marjan Van de Kauter | Els Lefever | Véronique Hoste
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

2014

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LT3: Sentiment Classification in User-Generated Content Using a Rich Feature Set
Cynthia Van Hee | Marjan Van de Kauter | Orphée De Clercq | Els Lefever | Véronique Hoste
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

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Evaluation of Automatic Hypernym Extraction from Technical Corpora in English and Dutch
Els Lefever | Marjan Van de Kauter | Véronique Hoste
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In this research, we evaluate different approaches for the automatic extraction of hypernym relations from English and Dutch technical text. The detected hypernym relations should enable us to semantically structure automatically obtained term lists from domain- and user-specific data. We investigated three different hypernymy extraction approaches for Dutch and English: a lexico-syntactic pattern-based approach, a distributional model and a morpho-syntactic method. To test the performance of the different approaches on domain-specific data, we collected and manually annotated English and Dutch data from two technical domains, viz. the dredging and financial domain. The experimental results show that especially the morpho-syntactic approach obtains good results for automatic hypernym extraction from technical and domain-specific texts.