Modeling for Crime Busting

The paper models for identifying people in a 83-workers-company who are the most likely conspirators. The train of thought is that: (1) get a priority list for valuing the suspicious degree of the workers, (2) get a line separating conspirators from nonconspirators, (3) get the leader of the conspiracy. The paper first sets different values of suspicious degree for messages with various features in order to value the suspicious degree of everybody. Secondly, we optimizes the primary figure by using a formula based on weighted average method. Thirdly, we worked through each individual on the better priority list from both ends. Then, the paper used some methods of semantic analysis to better distinguish possible conspirators from the others and finally got the priority list. Next, the discriminate line is determined by using probability theory and clustering analysis theory. At last, get the leaders by the priority list and discriminate line.

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