In this paper, we aim at detecting event-relevant sentences in a news corpus given an event query.
to previous work that needs expensive annotation for query-answer pairs, we use unlabeled news summaries that are readily available in large quantities online and design an efficient semi-supervised learning strategy for event identification based on co-training with Bayesian network classifiers.