Search Results for author: V

Found 38 papers, 1 papers with code

Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text

1 code implementation ACL 2019 Lukas Ruff, Yury Zemlyanskiy, V, Robert ermeulen, Thomas Schnake, Marius Kloft

There exist few text-specific methods for unsupervised anomaly detection, and for those that do exist, none utilize pre-trained models for distributed vector representations of words.

Contextual Anomaly Detection General Classification +3

Predicting Adolescents' Educational Track from Chat Messages on Dutch Social Media

no code implementations WS 2018 Lisa Hilte, Walter Daelemans, V, Reinhild ekerckhove

We aim to predict Flemish adolescents{'} educational track based on their Dutch social media writing.

What Action Causes This? Towards Naive Physical Action-Effect Prediction

no code implementations ACL 2018 Qiaozi Gao, Shaohua Yang, Joyce Chai, V, Lucy erwende

Despite recent advances in knowledge representation, automated reasoning, and machine learning, artificial agents still lack the ability to understand basic action-effect relations regarding the physical world, for example, the action of cutting a cucumber most likely leads to the state where the cucumber is broken apart into smaller pieces.

Poly-GrETEL: Cross-Lingual Example-based Querying of Syntactic Constructions

no code implementations LREC 2016 Liesbeth Augustinus, V, Vincent eghinste, Tom Vanallemeersch

We present Poly-GrETEL, an online tool which enables syntactic querying in parallel treebanks, based on the monolingual GrETEL environment.

Sentence Translation

AfriBooms: An Online Treebank for Afrikaans

no code implementations LREC 2016 Liesbeth Augustinus, Peter Dirix, Daniel van Niekerk, Ineke Schuurman, V, Vincent eghinste, Frank Van Eynde, Gerhard van Huyssteen

Compared to well-resourced languages such as English and Dutch, natural language processing (NLP) tools for Afrikaans are still not abundant.

Linking Pictographs to Synsets: Sclera2Cornetto

no code implementations LREC 2014 V, Vincent eghinste, Ineke Schuurman

Social inclusion of people with Intellectual and Developmental Disabilities can be promoted by offering them ways to independently use the internet.

Machine Translation Translation

A Method for Building Burst-Annotated Co-Occurrence Networks for Analysing Trends in Textual Data

no code implementations LREC 2014 Yutaka Mitsuishi, V{\'\i}t Nov{\'a}{\v{c}}ek, V, Pierre-Yves enbussche

This paper presents a method for constructing a specific type of language resources that are conveniently applicable to analysis of trending topics in time-annotated textual data.

On the origin of errors: A fine-grained analysis of MT and PE errors and their relationship

no code implementations LREC 2014 Joke Daems, Lieve Macken, V, Sonia epitte

In order to improve the symbiosis between machine translation (MT) system and post-editor, it is not enough to know that the output of one system is better than the output of another system.

Machine Translation Translation

Annotating Clinical Events in Text Snippets for Phenotype Detection

no code implementations LREC 2014 Prescott Klassen, Fei Xia, V, Lucy erwende, Meliha Yetisgen

Early detection and treatment of diseases that onset after a patient is admitted to a hospital, such as pneumonia, is critical to improving and reducing costs in healthcare.

Pneumonia Detection

Example-Based Treebank Querying

no code implementations LREC 2012 Liesbeth Augustinus, V, Vincent eghinste, Frank Van Eynde

The recent construction of large linguistic treebanks for spoken and written Dutch (e. g. CGN, LASSY, Alpino) has created new and exciting opportunities for the empirical investigation of Dutch syntax and semantics.

Large aligned treebanks for syntax-based machine translation

no code implementations LREC 2012 Gideon Kotz{\'e}, V, Vincent eghinste, Scott Martens, J{\"o}rg Tiedemann

We present a collection of parallel treebanks that have been automatically aligned on both the terminal and the nonterminal constituent level for use in syntax-based machine translation.

Language Modelling Machine Translation +1

Statistical Section Segmentation in Free-Text Clinical Records

no code implementations LREC 2012 Michael Tepper, Daniel Capurro, Fei Xia, V, Lucy erwende, Meliha Yetisgen-Yildiz

Automatically segmenting and classifying clinical free text into sections is an important first step to automatic information retrieval, information extraction and data mining tasks, as it helps to ground the significance of the text within.

General Classification Information Retrieval +4

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