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Iot based inventory management system with recipe recommendation using collaborative filtering

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TLDR
In this article, a recipe scoring algorithm that follows a collaborative filtering approach is proposed to score the recipes and the recipes that yield a higher score will be recommended to the user using the available inventory.
Abstract
The internet is a huge pool of data. It consists of various websites that provide numerous recipes and it becomes difficult for a person to manually search for a recipe based on the available ingredients daily. Inventory management is a difficult task because it is not feasible to keep track of every food ingredient. The objective of this paper is to provide an effective solution to manage inventory of the user using the Internet of Things (IoT) as well as recommending a recipe to the user using the available inventory. A recipe scoring algorithm that follows a collaborative filtering approach is proposed to score the recipes and the recipes that yield a higher score will be recommended to the user. This reduces the time and efforts of the user which makes the system more efficient and user-centric.

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References
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Journal ArticleDOI

Web scraping technologies in an API world

TL;DR: This article reviews existing scraping frameworks and tools, identifying their strengths and limitations in terms of extraction capabilities and describing the operation of WhichGenes and PathJam, two bioinformatics meta-servers that use scraping as means to cope with gene set enrichment analysis.

Collaborative Filtering Based Recommendation System: A survey

TL;DR: This paper has categorized collaborative filtering recommendation system and shown how the similarity is computed, and types of rating that can be collected from the user to rate items are discussed along with the uses.

Recipe Recommendation Method by Considering the User's Preference and Ingredient Quantity of Target Recipe

TL;DR: In order to reflect the truly user's preferences, this work proposes a scoring method of cooking recipes based on user's food preferences and the quantity of the ingredient in a recipe.
Book ChapterDOI

Machine Learning Based Food Recipe Recommendation System

TL;DR: Two approaches to recommend recipes based on preferences of the user given in the form of ratings are presented and compared to identify which approach suits the dataset better.
Proceedings ArticleDOI

IoT based grocery monitoring system

TL;DR: Using this prototype as a base, real-time applications can be developed to manage the current inventory efficiently with its implications in food and e-commerce industry.
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The paper proposes an IoT-based inventory management system that uses collaborative filtering to recommend recipes based on the available ingredients.

What are the challenges of using a recommendation system for inventory management and promotion planning?

The challenges of using a recommendation system for inventory management and promotion planning are not mentioned in the provided information.