Recurrent Pattern Analysis with Data Slicing and Conceptual Model Used for Supervision based Data Modelling

The data which is going to be obtained from any standard theory set can be used for various management needs based upon which the decision can be taken and the same decision which is going to be used for any purpose. The major decision-making system for any commerce or management related issues the gathered data is firstly classified based upon its intents. The intents which are used for passing the data or the information pertaining to the contents and the broadcast system will be very much useful for the start-ups where all the real time challenges which a beginners may face before the startups can be minimized. The proposed techniques of the data partition can be done based upon the frequently or recurrent pattern. The recurrent pattern discovery based upon the partition made makes the tasks of the decision support and data mining based on slicing provides the easy way to use the analytics in the area of management. The slicing can be done based upon various attributes or the required parameters which forms the base of the context and the organizational goals. To enhance the security measures the quasi attributes can be used in the concept to be identified as the process knowledge management. The integration of the data will be provided based upon the organizational contexts to justify the cognitive approach and the sliced constructs of the available data to reach to exhibit the significant chain of identifying the extraction of the pure data and the analysis of the obtained determinants of the generalized and the bucketized data can be easily done.