@inproceedings{ribeiro-etal-2017-unsupervised,
    title = "Unsupervised Event Clustering and Aggregation from Newswire and Web Articles",
    author = "Ribeiro, Swen  and
      Ferret, Olivier  and
      Tannier, Xavier",
    editor = "Popescu, Octavian  and
      Strapparava, Carlo",
    booktitle = "Proceedings of the 2017 {EMNLP} Workshop: Natural Language Processing meets Journalism",
    month = sep,
    year = "2017",
    address = "Copenhagen, Denmark",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W17-4211/",
    doi = "10.18653/v1/W17-4211",
    pages = "62--67",
    abstract = "In this paper, we present an unsupervised pipeline approach for clustering news articles based on identified event instances in their content. We leverage press agency newswire and monolingual word alignment techniques to build meaningful and linguistically varied clusters of articles from the web in the perspective of a broader event type detection task. We validate our approach on a manually annotated corpus of Web articles."
}