Cooking Recipe Rating Based On Sentiment Analysis

Download Document/Synopsis
You will find number of recipe online. Some might be correctly posted some may not. Recipes what you read will not be the same what you find after preparation. There are number of recipes you will find online which are incorrect. So in order to get right recipes, recipes must be rated by the user. Here we propose a system where user can select categories and post the recipes. Recipes are rated and commented by the visitors. So that user may end up by finding correct recipe online. We will apply sentiment analysis and text summarization approach to mine data. Sentiment analysis is a machine learning approach in which machine learns and analyze the sentiments, emotions etc about some text data like reviews about recipes. In Text summarization, importance of keywords is decided based on linguistic features of keywords. In this system, admin will add keywords which are relevant to the recipes. System will find those keywords in comment posted by visitor and system will rate the recipe accordingly. Based on visitors review, system will rate the recipe. So it made easier for visitor to get correct recipe. This system is helpful for many visitors who look for recipes online.



Advantages
  • User will get correct recipes.
  • Effective graphical user interface
  • User will get genuine rating of the recipes.
  • User can easily find recipes.
Disadvantages
  • Users who don’t have internet connection can’t access the system.
  • System can mine keywords rather than phrase
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