no code implementations • WS (NoDaLiDa) 2019 • Astrid van Aggelen, Antske Fokkens, Laura Hollink, Jacco van Ossenbruggen
Determining how words have changed their meaning is an important topic in Natural Language Processing.
no code implementations • 3 May 2024 • Sanne Vrijenhoek, Savvina Daniil, Jorden Sandel, Laura Hollink
Diversity is a commonly known principle in the design of recommender systems, but also ambiguous in its conceptualization.
no code implementations • 3 May 2024 • Manel Slokom, Laura Hollink
Our approach employs a user-centric pre-processing strategy aimed at exposing users to a wide array of content categories and topics.
1 code implementation • 13 Nov 2023 • Andrei Nesterov, Laura Hollink, Jacco van Ossenbruggen
In some cases, LOD contributors mark contentious terms with words and phrases in literals (implicit markers) or properties linked to resources (explicit markers).
2 code implementations • 1 Sep 2022 • Savvina Daniil, Mirjam Cuper, Cynthia C. S. Liem, Jacco van Ossenbruggen, Laura Hollink
We find that popular books are mainly written by US citizens in the dataset, and that these books tend to be recommended disproportionally by popular collaborative filtering algorithms compared to the users' profiles.
no code implementations • 25 Oct 2019 • Laura Hollink, Aysenur Bilgin, Jacco van Ossenbruggen
The "basic level", according to experiments in cognitive psychology, is the level of abstraction in a hierarchy of concepts at which humans perform tasks quicker and with greater accuracy than at other levels.
1 code implementation • 1 Oct 2018 • Aysenur Bilgin, Laura Hollink, Jacco van Ossenbruggen, Erik Tjong Kim Sang, Kim Smeenk, Frank Harbers, Marcel Broersma
With the growing abundance of unlabeled data in real-world tasks, researchers have to rely on the predictions given by black-boxed computational models.
no code implementations • LREC 2016 • Laura Hollink, Adriatik Bedjeti, Martin van Harmelen, Desmond Elliott
The corpus consists of JSON-LD files with the following data about each article: the original URL of the article on the news publisher{'}s website, the date of publication, the headline of the article, the URL of the image displayed with the article (if any), and the caption of that image.