Bibliographic description:
Antypova Alisa. Language-Agnostic detection of Current Events across Wikipedia. Master Thesis. Ukrainian Catholic University, Faculty of Applied Sciences, Department of Computer Sciences. Lviv 2023, 46 p.
Abstract:
Currently, English Wikipedia alone includes over 6,660,000 articles and it averages
550 new articles per day. To assist the readers in identifying pages that cover recent
noteworthy occurrences the Current Events portal was implemented. However, this
portal is maintained manually with notable quality differences across languages.
The main goal of this work is to establish the task of supervised event detection in
Wikipedia and propose a language-agnostic solution to address this problem. This
is an important milestone towards improving the quality of the Current Events Portal
for the languages with not many active editor communities. In this work, we
reviewed existing research on this topic, and by combining and enriching those existing
solutions, we proposed a current event detection dataset based on the Current
Events Portal updates and Wikipedia pages’ features. Also, we developed a
language-agnostic event detection model and reported its performance in English,
German, and Polish languages, showing that is possible to automatize this task. The
outcome of this work can be used to assist Wikipedia editors to keep the Current
Event portal updated, saving time and the human effort used on this task.
