<h1 style=”font-size: medium;”>Abstract:</h1>
The main aim of Efficient Utility Mining for Nutrition Calculation project is to mine the frequent itemset and maximum threshold signature of the Health life food suggestion. And to find the maximum threshold signature of the Health life food suggestion. The frequent item set deals with the whole database of the shopping application and predict the health condition. It contains various transactions like sales data, purchase data, customer data, item data, and calorie details, etc.
Here enhanced EHAUPM (Enhanced Efficient High Average-Utility Pattern Mining) Item set implemented. Efficient Utility Mining for Nutrition Calculation performs more accuracy and performance than TKU (mining Top-K Utility item sets) and TKO (mining Top-K utility itemsets in One phase). These methods implemented in the existing methods for mining such item sets without the consideration of the entire database. This may cause inaccurate results and improper output.
Primary Objectives.
- The main aim of Efficient Utility Mining for Nutrition Calculation project is to mine the frequent itemset and maximum threshold signature of the Health life food suggestion.
- The suggestions and predictions will be generated through the purchased data and calorie chart.
- Here EHAUPM – Enhanced Efficient High Average-Utility Pattern Mining for efficient data retrieval.
- A new concept called data engineering is used in the system to find associations with the calories used and generate some health tips.
- Rule Mining Concepts like Association rules has been implemented to make the result much better
- All the result will be shown in chart and graph
Keywords:
Data mining, Utility Mining, Nutrition calculation, Efficient High Average-Utility Pattern Mining, Data Engineering, Association Rules, Shopping Application, Health care, IT projects, CSE projects, Engineering projects.
Helpline:
Visual Studio – 2012, ASP.NET, C#, SQL Server, Java Script.
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