Identifying Principals and Accessories in a Complex Case based on the Comprehension of Fact Description
In this paper, we study the problem of identifying the principals and accessories from the fact description with multiple defendants in a criminal case. We treat the fact descriptions as narrative texts and the defendants as roles over the narrative story. We propose to model the defendants with \textit{behavioral semantic information} and \textit{statistical characteristics}, then learning the importances of defendants within a learning-to-rank framework. Experimental results on a real-world dataset demonstrate the behavior analysis can effectively model the defendants{'} impacts in a complex case.
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