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洞見 - Crime Prediction
Modeling Intensive Intent Dynamics for Accurate Fine-grained Sequential Crime Prediction
The core message of this article is to propose a novel fine-grained sequential crime prediction framework, CrimeAlarm, that effectively models the intensive intent dynamics by employing a novel mutual distillation strategy inspired by curriculum learning.
Empirical Analysis of Crime Prediction Techniques
The author proposes a methodological taxonomy to classify crime prediction algorithms, enhancing comparability and aiding in algorithm development.
