Call-of-Project matching_and_recommendation_service

Author: Emir KAFADAR

Due to insufficient data, we didn't use machine learning and artificial intelligence for this project. Instead, we utilized the Python set data structure to suggest projects to users and to match them with each other. However, if the Call-of-Project project grows and we have enough data, we might consider incorporating machine learning and AI.

The Call-of-Project project connects to this service using a feign-client to retrieve the necessary IDs (matching user IDs and suggested project IDs). It then transforms the projects within its system into a format that users can see. This information is then delivered to users via email at specific times and days of the week, using a scheduler service.

Architecture

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• This diagram shows how the match-and-recommendation service interacts with the Call-of-Project project.

Example Emails

• Project Recommendation

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• User Matching:

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