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Hive app Recommendation system

Welcome to Hive App's recommendation system, an AI algorithm that's implemented to enhance the functionality of the app and to give the users better and easier experience.


System Overview

Objective

The recommendation system targets predicting each user's favourite place to study or finish his/her work.

System phases

This system comes at two phases:

1. Content-based filtering

At the launch stage we doesn't have many ratings to use it in recommendations. Here, the content-based filtering is used as it recommend the most suitable places from users preferences and workspaces/sharespaces ratings in the same preferences. This comes as a priliminary solution until the users ratings are available

We decided to use euclidean distance instead of cosine similarity as it's suitable for numerical data where the magnitude of differences matters.

2. Collaborative filtering

Soon this section will be launched

Technologies Used

  • Python: Programming language.
  • Pandas: Python library for data manipulation.
  • Numpy: Python library for mathematical operations.
  • Scikit-learn: for ML metrics and operations.
  • Jupyter notebook: Programming Environment.

Thank you for exploring the Hive App! We are excited to help you find the ideal workspace or study environment that meets your needs with cutting-edge technology and a user-centric approach. For further information or inquiries, feel free to reach out to our team members.

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