Reference no: EM131303722

Data Structures and Algorithms Project

Introduction

For the semester project, you will be implementing an item-based recommendation system. Recommendation systems are widely used on the web for recommending products and services to users based on their past actions and interaction with the system. Recommendation systems have important applications in several areas, such as:

• Product recommendation. Amazon and ebay provide recommendations to you based on your purchase history. Facebook recommends friends. Dating websites recommend dating partners, etc.
• Movie recommendation: Netflix offers its customers recommendations of movies they might like. These recommendations are based on ratings provided by users. In fact, the importance of predicting ratings accurately is so high, that Netflix offered a prize of $1M to the first algorithm that could beat its own recommendation system by 10%.
• News Articles: News services recommends news articles to the readers based on the articles that they have read in the past.

What is the input to recommender system?

What should be the output of recommender system?

Predicting movie ratings using an item-based recommender system?

Team Work:

You may form a team of two and do the do the final project together. If you like to team up with another classmate, please read the following instructions carefully:

1. You may use our class slack channel to find another classmate and form a team.

2. Once you choose your team email me the name and github id of the team members.

3. Every team must collaborate and submit their work on github. Submitting on github is mandatory for each team. This is a good practice to experience industry standard collaborative software development.

4. I will create github repository and a private slack channel for each team. I will integrate your github repository with your slack channel so you use the channel for private team communication and get notifications of changes on your repository (commit, push, etc.)

5. Each team is responsible for distributing the work evenly. There is no guarantee that both team members will receive the same grade. If one team member does all the work and commits everything to the repository, then he/she will not get the same grade as the other member who did not commit anything. With every commit, you should include a description of the changes you made in your code.

What you need to submit:

1- All your java files. Please make sure to include comments in your code to make it understandable

2- A readme file including a general description of your files.

3- A document explaining the following:

a. Data structures that you used to store movie information and ratings and the algorithm that you used to compute the top 5 recommendation.

b. Analysis of the order of magnitude efficiency (big -Oh) of your algorithm in terms of the number of users, and movies. Briefly explain how you derived the big-Oh.

Attachment:- Assignment.rar