Data Standardization Using Hidden Markov Model

Record linkage is the process of connecting the data which will be having the same entities in one or more data collections. This case can be achieved if there is a unique identity. If not then the user needs to enter the details randomly and then standardize it through some process called as standardization. This can be achieved through data standardization using hidden Markov Model application. People can rely on this application without any difficulty. This will be one of the applications that one can work on and implement in real time world. There will be one user to this system that is the admin.

The admin can enter the data randomly in the application. In order to achieve the task Markov Model is used. Then using the use of this application, the data will be classified easily as to which field must contain which data and will be provided as output. The work of the admin will be made easier through the use of this application. Raw sequence data can be used easily in order to get the proper data without any difficulty and with great ease. The features that can be included in data standardization using hidden Markov Model application are as follows:

  • Raw sequence data: Efficient learning algorithm can take place using raw sequence data.
  • Flexible: This can help in taking flexible generalization.
  • Variety of applications: This project can help the wide variety of fields to use it.
  • Saves time: This application can help in saving time since there is no need to check for the data that is standard through this application.
  • Easy access: This application can be accessed anytime and anywhere from the world.
  • User friendly: This application will be user friendly since the user interface will be simple and easy to understand even by the common man.





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