Russian News Clustering and Headline Selection Shared Task
This work addresses the need for better natural language processing tools for Russian news analysis, though it is incremental as it builds on existing shared task frameworks.
The paper tackled the problem of organizing Russian news by introducing tasks for event detection, headline selection, and headline generation, along with the first public Russian datasets for event detection and headline selection, and a novel headline generation dataset with multiple reference headlines per cluster.
This paper presents the results of the Russian News Clustering and Headline Selection shared task. As a part of it, we propose the tasks of Russian news event detection, headline selection, and headline generation. These tasks are accompanied by datasets and baselines. The presented datasets for event detection and headline selection are the first public Russian datasets for their tasks. The headline generation dataset is based on clustering and provides multiple reference headlines for every cluster, unlike the previous datasets. Finally, the approaches proposed by the shared task participants are reported and analyzed.