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A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events
2016
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16
State-of-the-art event encoding approaches rely on sentence or phrase level labeling, which are both time consuming and infeasible to extend to large scale text corpora and emerging domains. Using a multiple instance learning approach, we take advantage of the fact that while labels at the sentence level are difficult to obtain, they are relatively easy to gather at the document level. This enables us to view the problems of event detection and extraction in a unified manner. Using distributed
doi:10.1145/2983323.2983821
dblp:conf/cikm/0064NRR16
fatcat:q64ozniftbbbrmil4ekohj3xya