We can find a number of food and cooking recipes online. Among which some recipes are correctly posted and some are not. The food may not seem same after preparation which you have prepared by reading a particular food recipe. So, in order to get appropriate food recipes, recipes must have good ratings from readers. In this .net project we develop a system where user can select categories and post the recipes. Food recipes posts are rated and commented by the readers. The ratings and comments help the users to find the correct recipes. In this project we use emotional analysis which is a machine learning approach to mine data. Emotional analysis is a technique in which machine learns to analyse the sentiments, emotions and much more about text data like reviews about recipes. In Text Summarization process the importance of keywords are decided based on linguistic features of the keywords. In this food rating system, admin will add keywords which are related to cooking recipes. The system will find all those keywords in the comments posted by the users and the system will automatically rate the recipe. So, the system will rate the recipes based on user reviews. This system is a great help for those who look for recipes online.
- Users can get a plenty of high rated food recipes
- Users will get correct recipes
- Effective and easy graphical user interface
- Users will get genuine rating of the recipes
- Users can easily find or search for a recipe
- Application requires active internet connection
- Users need to enter correct input or the system will behave abnormally