人工智能-数据分析-面向侦查的快递数据分析挖掘系统.pdf
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ABSTRACT
In the end of 2011,there are more than 7500 companies which had business
permit of express service in China.With the fast development in these years,express
service has become a part of people’s living,that makes a new style of offence.How to
unearth deeply in the express data,then find the statement and exculpations of a
suspect and defendant,become a task of police work.In the background of express
service and the behavior of the statement and exculpations of a suspect and
defendant ,this thesis will use Classification data mining technology to research the
purpose of the expess data in the criminal act.
The research priorities is to combine the express data and the requirement of
police work,structure the data warehouse of police work, analyses the internal
connecting link of the statement and exculpations of a suspect and defendant hiding in
the express data by OLAP and analysis of clustering algorithm,to contrast the similar
and otherness analysis like early warning and suspicious alignment.The main research
like:
1.Sampling the data of secial people from the express data,build a model of
analysis and mining,analyse and mining deeply with manual basis in multiple
dimensions and perspectives,analyse the communication traits,and reveal in
graphical,easy,visual and easy way to understand.
2.Use several algorithm to train the sample data,choose one or several algorithm
that in the highest accuracy rate to analyse and forecast the new data.use the model
after verification to mining the potential rules and search in the express database,mark
the target in high similarity, narrow the scope of criminal,use network analysis
algorithm to analyse the relative network of special people,and mining the
accomplice.
3.The system can also summarize the criminal of the same kind,add express
information of them,join to train and update the model, keep the model new.
Prevention of crime is possible by using the system,it is also useful to analyse and
response and attack to the crime quickly.
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