Mining Popular Crime Patterns in Incremental Databases
نویسنده
چکیده
The Crime investigation department have very significant role in police system in all countries in the world. Computer systems are placed in almost all police stations to store and retrieve the crimes and criminal data and for subsequent reporting. For crime analysts, it is a challenging, time-consuming to determine who have been committed crimes from the large set of crimes that are happening every year. Our goal is to identify recent popular crime patterns from large set of crime databases that are updating every day. To do this, we are proposing a popular crime pattern detection algorithm from incremental crime databases. Such data mining technologies are helpful to design proactive services to reduce crime incidences in the police stations jurisdiction. Our experiment results show the efficiency in time consuming for mining popular crime patterns.
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