In our hectic daily lives, we frequently forget to buy groceries. It is not uncommon for us to decide to make a recipe only to discover that we lack all of the necessary ingredients, forcing us to either abandon the plan or pay a higher price for the ingredients. To tackle this issue in general, we present a website that analyzes users' weekly meal plan and assists him in following it in a most efficient way.
Aim: To create a web application for maintaining and analyzing a user's weekly meal schedule, as well as assisting him with it by suggesting the recipe, listing the ingredients needed, and providing their current prices, as well as interactively assisting him in preparing the dish by reading out the recipe to him.
We all have a foodie inside us, and with this nature comes cravings for various dishes. But, due to our hectic daily schedules, whenever we decide to cook a meal, we find ourselves in a situation where we lack all of the ingredients needed to prepare the dish, and we end up canceling the plan. But what if we had a website that would take our weekly schedule and suggest a recipe with a list of all the ingredients needed? This would relieve us of a lot of work and allow us to enjoy our favorite dishes.
We have developed a website that allows users to maintain a weekly meal schedule, and the website will check available recipes for preparing the dish and will list down the necessary ingredients. It will then fetch the prices of the items on the list across a shopping site and display them so that the users can add them to the cart.
We are further using a LDA model that will make recipe recommendations based on the user's preferences. We intend to analyze different recipes' datasets based on various parameters such as the type of ingredients, the number of steps in the recipe, the number of ingredients, user reviews and ratings, and provide personalized recommendations. We are doing topic modelling to provide personalized recommendations.
To make it more interactive, we added a feature in which we developed a personal assistant bot that would interact with users in real-time and read out the recipes to them. This would assist the user to follow any recipe, without the need of him actually reading it.
Current Solutions:
Food.com is a pre-existing food-recommendation service. It organizes recipes into categories such as popular, breakfast & brunch, and so on. Such pre-existing food/recipe recommender systems, meanwhile, make suggestions based on the tastes of consumers as well as their dietary requirements. They do not, however, offer a weekly meal plan based on the user's food preferences. Further, they do not provide the current price of each ingredient.
