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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | Film Saga- A Movie Recommendation System Using Machine Learning |
| Authors Name: | Namyapriya Dayananda |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_183251
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| Published Paper Id: | IJRTI2207198 |
| Published In: | Volume 7 Issue 7, July-2022 |
| DOI: | |
| Abstract: | Technically nowadays there is a rapid widening when it comes to the field of Data Science, Machine learning, Deep learning and Artificial Intelligence. Data acquisition is more efficient through the recommendation systems. The Recommender engines or recommendation systems are the major wing of Data Analytics, Machine learning algorithms and Artificial intelligence which is conducted by the software engineers to improve the quality of searching results and predicts the users’ ratings / rankings on a particular item/ product or commodity, then offers relevant recommendations to the users and returns back the user’s preferences. Theses recommender systems entice users with enhanced experience and pure joy. In this project work is a Movie recommender system is built by loading the datasets from Kaggle Website, then various filtering algorithms like demographic filtering, Content-based filtering, emotion / mood-based filtering through web scraping methodologies are used which makes recommendations based on the users’ preferences, rating, genre, matching the terms, experiences, emotions, popularity and collects information to eventually extract the final movie recommendation systems. In this project both personalized (user specific) and non-personalized (common) recommendations are processed. Furthermore, the output is extracted through the Flask Micro Web framework written upon python programming to develop the web application and then its transformed into a Mobile application through the React front-end JavaScript for user Interfaces/ User experiences (UI/UX) for the recommender system. |
| Keywords: | Emotion Based, Recommendation System, Web Framework, Content Based Filtering, Demographic Filtering |
| Cite Article: | "Film Saga- A Movie Recommendation System Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 7, page no.1263 - 1267, July-2022, Available :http://www.ijrti.org/papers/IJRTI2207198.pdf |
| Downloads: | 000204911 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2207198
Registration ID:183251
Published In: Volume 7 Issue 7, July-2022
DOI (Digital Object Identifier):
Page No: 1263 - 1267 Country: Bangalore, Karnantaka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2207198 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2207198 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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