Chennai Event Show AI: An Intelligent Event Aggregation and Recommendation System Using Machine Learning
Abstract
The dissemination of urban event information in urban areas is usually spread through various electronic platforms, which makes the dissemination of information incomprehensive and discoverable to the user. Current event listing systems are mostly static listing systems that are slightly automated and personalized. The paper will suggest Chennai Event Show AI, an AI-based event aggregation and recommendation system that fits the city of Chennai. The system uses the automated web scraping of online sources to gather event information to continuously update, and then classifies and tags event information with the help of AI on a Large Language Model (Google Gemini 1.5 Flash) around LangChain. A query interpretation agent takes the natural language user inputs and dynamically creates structured MongoDB queries to find the relevant events. The system is deployed on FastAPI as backend services, MongoDB as storage, React as the frontend, and APScheduler to update the data periodically. Experimental data show that there is better relevance of event retrieval, less effort of manual search and better personalization when compared to the traditional listing methods. The suggested framework proves the relevance of AI.