Closed prernasahuu closed 3 months ago
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PLEASE DO ASSIGN ME THE PROJECT AS I AM A CONTRIBUTOR IN GSSoC'24.
thank you for assigning this project.
Hey @sanjay-kv, can you please assign me this issue?
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Describe the bug The current review scraping process in the IMDb ratings system exhibits certain inaccuracies, particularly in distinguishing between valid and fake user actions. Addressing this issue is crucial for maintaining the integrity of the review data. Additionally, IMDb’s movie recommendation system requires enhancement to provide more precise and personalized recommendations based on user preferences. I goal for this project to improve the recommendation system using various machine learning techniques and Python programming, while also implementing a robust classification mechanism to differentiate between genuine and fraudulent reviews. The final results will be exported in CSV format for further analysis To Reproduce Steps to reproduce the behavior: Scraping Reviews: 1.Using Python libraries like BeautifulSoup to load IMDb pages.
Expected behavior I have expected to fix the bugs and make the review scraping system precision and accuray rate to be more high.
Desktop (please complete the following information):
Smartphone (please complete the following information):
Additional context we can also add features like: advertising the better movie option for the user with bad experience. also, to conduct some interactive sessions to seek more attention and empower the IMDb promotions. the sessions can be like: movie quizs, riddles, funny facts and myth brusters etc.. just to have more interaction with users and make users participation higher. PLEASE PULL UP THE REQUEST FOR THE PROJECT. OPEN TO ANY SUGGESTION OR IDEAS.
I am a Contributor in GSSoc'24