Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3158
Title: Recommendation system based on Tamil-English code-mixed text analysis
Authors: Vijayakumar, S
Murugaiah, G
Sivanesan, J
Archchana, K
Tissera, W
Vidhanaarachchi, S
Keywords: Decryption
Encryption
Language prediction
NLTK
Sentiment analysis
Tanglish
Translation
Issue Date: 15-Oct-2022
Publisher: Institute of Electrical and Electronics Engineers
Citation: S. Vijayakumar, G. Murugaiah, J. Sivanesan, K. Archchana, W. Tissera and S. Vidhanaarachchi, "Recommendation system based on Tamil-English code-mixed text analysis," 2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 2022, pp. 0378-0383, doi: 10.1109/IEMCON56893.2022.9946465.
Series/Report no.: 2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2022;Pages 378 - 383
Abstract: The cinema industry has always been popular since its inception many years ago and is a preferred pastime of many people. It can be observed that even though online movie applications are popular in multilingual society, English is the preferred language. Naturally, people of other languages mix their native language with English during communications resulting in an abundance of multilingual data called code-mixed data, available in today's world. This research focuses on the movie recommendation system whose primary objective is to make a recommender system through Natural Language Processing (NLP) Tools for Tamil-English Code-mixed (Tanglish) Comments. Our recommendation system will be a filtering scheme whose primary objective is to predict a viewer's rating or preference towards a movie or web series.
URI: https://rda.sliit.lk/handle/123456789/3158
ISSN: 978-166546316-4
Appears in Collections:Department of Information Technology

Files in This Item:
File Description SizeFormat 
Recommendation_system_based_on_Tamil-English_code-mixed_text_analysis.pdf
  Until 2050-12-31
529.81 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.