Food Recipes Rating System Based on Emotional Analysis

A .NET recipe site that rates recipes automatically from comments. Emotional analysis finds positive and negative words in users' comments and calculates each recipe's rating.

Data is collected from the source and stored in a database. It is pre-processed: cleaned, integrated and transformed. A mining algorithm (classification, clustering or association rules) finds patterns. Results are shown as charts and reports that help the user make decisions.

It finds frequent itemsets in transaction data by building larger itemsets only from smaller ones that are already frequent, and then derives association rules with support and confidence above set thresholds.

Web Forms uses server controls and view state with an event model. MVC separates Model, View and Controller, gives full control over HTML and is easier to test.

We followed an iterative (incremental) model: requirements and a basic design first, then modules built and tested one by one, with the guide's feedback after each review. It suits a project where requirements become clearer as we build.

Unit testing of each module, integration testing of the complete flow and system testing with real inputs. Test cases with expected and actual results are listed in the report, including invalid inputs.

The current version is tested on a limited dataset or number of users. Future work includes deploying on the cloud, adding more features or languages, improving accuracy with more data and building a mobile version.