https://github.com/peteprattis/k-nearest-neighbors-algorithm-and-rating-prediction

A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user with only a few non zero ratings of some locations, find the k nearest neighbors through similarity score and then predict the ratings of the new user for the non rated locations.
https://github.com/peteprattis/k-nearest-neighbors-algorithm-and-rating-prediction

computer-science console-application cosine-similarity euclidean-distance java k-nearest-neighbours knn manhattan-distance program recommendation-system recommender-system similarity student

Last synced: about 1 month ago
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A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user with only a few non zero ratings of some locations, find the k nearest neighbors through similarity score and then predict the ratings of the new user for the non rated locations.

• Host: GitHub
• URL: https://github.com/peteprattis/k-nearest-neighbors-algorithm-and-rating-prediction
• Owner: PetePrattis
• License: mit
• Created: 2019-12-16T12:32:29.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2019-12-18T11:48:23.000Z (about 5 years ago)
• Last Synced: 2023-09-14T10:17:26.117Z (over 1 year ago)
• Topics: computer-science, console-application, cosine-similarity, euclidean-distance, java, k-nearest-neighbours, knn, manhattan-distance, program, recommendation-system, recommender-system, similarity, student
• Language: Java
• Homepage:
• Size: 21.5 KB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# A Java Program / Project

**This is a java project from my early days as a Computer Science student**

_This programm was created for my thesis project

and is a test program implementing knn algorithm to use as a template for my thesis project_

> #### Description of project

>

>>A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user with only a few non zero

ratings of some locations, find the k nearest neighbors through similarity score and then predict the ratings of the new user for the non rated locations.

> #### Impementation of project

>

> 1. Implementing knn algorithm using these heuristics for similarity score:

>> - Cosine similarity

>> - Euclidean distance 

>> - Manhattan distance

>

> 2. Using the ratings of the k nearest neighbours the system recommends some non-rated-locations ratings

> #### About this project

>

> - This is a test project and an effort to implement the knn algorithm using a variety of heuristics for similarity score

> - The comments to make the code understandable, are within the .java archive

> - This project was written in Eclipse Java IDE

> - This repository was created to show the variety of the work I did and experience I gained as a student

>