Enhancing Event Exploration and Engagement: A Social Events Networking Platform Leveraging Cosine Similarity Recommendations and Google Maps Integration

Abstract

This project introduces a Social Events Networking Platform, strategically engineered to streamline event exploration and engagement through the effective utilization of user preferences. With a comprehensive range of functionalities, users can seamlessly navigate and participate in diverse events, while event planners gain the ability to create and manage their own events. At its core, the platform employs cosine similarity recommendation algorithms to analyze user preferences, providing personalized event suggestions tailored to individual likes and interests. This approach significantly heightens the probability of user attendance and interaction. In tandem with the recommendation feature, the platform seamlessly integrates Google Maps API, offering a map functionality that enables users to visualize event locations alongside pertinent details. This feature empowers users to efficiently plan their attendance by considering factors such as proximity and accessibility. The overarching goal is to cultivate a vibrant, interactive community by connecting event enthusiasts with organizers. The platform's reliance on Firebase Cloud Function APIs for CRUD operations, such as post creation, reading, updating, and deletion, ensures robust support. Additionally, the recommendation function, based on cosine similarity, is deployed as an API to Firebase Cloud Function. These APIs empower administrators to perform CRUD operations on events, while users can access events based on location and receive recommendations rooted in their favorite events. By seamlessly integrating event recommendations and location-based information, the platform elevates the overall event discovery and participation experience, rendering it more engaging and personalized for users.