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This is our project which we completed in 24 hours for Dragon Hackathon in University of Ljubljana. Project includes, network analysis, streamlit, LLM to build a chat bot and prompt engineering.

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ahbis99/movie_recommendation_system

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Movie Recommender System

This is our project which we finished in 24 hours for Dragon Hackathon in University of Ljubljana.

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General info

This project aims to simplify the process of choosing movies for viewers. Making a decision on which movie to watch can often be time-consuming, so our project streamlines this experience. The main screen offers two options: the first provides 10 random movie recommendations, while the second allows users to specify actor, category, or language preferences (up to 3 selections in any combination) to receive tailored recommendations. These recommendations are generated using an adjusted pagerank algorithm applied to an affiliation network.

Upon receiving recommendations, users can click on a movie title to open a new page featuring a chatbot. Initially, the chatbot provides general information about the selected movie. Users can continue interacting with the chatbot to ask additional questions about the movie.

This project's flexibility extends beyond movie recommendations; it can be adapted to offer recommendations in any domain where affiliation network data is available.

Technologies

Project is created with Python. The main packages used:

  • Langchain (LLM)
  • Numpy (Data analysis and cleaning)
  • Crewai (Crawling Internet for Chatbot)
  • Networkx (Network analysis)
  • Streamlit (Web application)

Visualizations from project

Visualization of the Webapp

Main Screen

Ekran Resmi 2024-04-23 20 05 24

Tailored Recommendations

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Chatbot

Ekran Resmi 2024-04-23 20 08 54 Ekran Resmi 2024-04-23 20 09 42

About

This is our project which we completed in 24 hours for Dragon Hackathon in University of Ljubljana. Project includes, network analysis, streamlit, LLM to build a chat bot and prompt engineering.

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