TLDR: Parallelizing the FP Growth Algorithm which is used in various data mining applications. This project was developed as a part of our course IT494 Big Data Processing. The traditional FP-Growth ...

Mining the FP-tree: The algorithm then recursively explores the FP-tree to find frequent itemsets, without needing to generate and test candidate sets. Efficient for Large Datasets: FP-Growth is known ...

This paper proposes an innovative solution to forge a resilient Food Recommendation Engine framework that would be able to make prediction as a set of five items as recommendation for each sold item ...

Now let’s have a look at FP Growth Algorithm. Frequent Pattern Growth Algorithm. As we have seen in the Apriori algorithm that it was generating the candidates for making the item sets. Here in the FP ...

Customizing the eating experience through personalized food recommendations has become crucial in the dynamic restaurant industry. Conventional recommendation systems often struggle to meet individual ...