News Across Languages - Cross-Lingual Document Similarity and Event Tracking (Extended Abstract)

News Across Languages - Cross-Lingual Document Similarity and Event Tracking (Extended Abstract)

Jan Rupnik, Andrej Muhič, Gregor Leban, Blaž Fortuna, Marko Grobelnik

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Journal track. Pages 5050-5054. https://doi.org/10.24963/ijcai.2017/720

In today's world, we follow news which is distributed globally. Significant events are reported by different sources and in different languages. In this work, we address the problem of tracking of events in a large multilingual stream. Within a recently developed system Event Registry we examine two aspects of this problem: how to compare articles in different languages and how to link collections of articles in different languages which refer to the same event. Building on previous work, we show there are methods which scale well and can compute a meaningful similarity between articles from languages with little or no direct overlap in the training data.Using this capability, we then propose an approach to link clusters of articles across languages which represent the same event.
Keywords:
Natural Language Processing: NLP Applications and Tools
Natural Language Processing: Sentiment Analysis and Text Mining