76 citations · 79 across the 2 of their papers we have counts for
5 papers
Embarrassingly Simple Unsupervised Aspect Extraction
Stéphan Tulkens, Andreas van Cranenburgh
We present a simple but effective method for aspect identification in sentiment analysis. Our unsupervised method only requires word embeddings and a POS tagger, and is therefore s…
A Short Review of Ethical Challenges in Clinical Natural Language Processing
Simon Šuster, Stéphan Tulkens, Walter Daelemans
Clinical NLP has an immense potential in contributing to how clinical practice will be revolutionized by the advent of large scale processing of clinical records. However, this pot…
A Dictionary-based Approach to Racism Detection in Dutch Social Media
Stéphan Tulkens, Lisa Hilte, Elise Lodewyckx +2
We present a dictionary-based approach to racism detection in Dutch social media comments, which were retrieved from two public Belgian social media sites likely to attract racist…
Using Distributed Representations to Disambiguate Biomedical and Clinical Concepts
Stéphan Tulkens, Simon Šuster, Walter Daelemans
In this paper, we report a knowledge-based method for Word Sense Disambiguation in the domains of biomedical and clinical text. We combine word representations created on large cor…
Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource
Stéphan Tulkens, Chris Emmery, Walter Daelemans
Word embeddings have recently seen a strong increase in interest as a result of strong performance gains on a variety of tasks. However, most of this research also underlined the i…