Open AccessMovie Recommendation Systems using Sentiment Analysis and Cosine Similarity
Author(s) -
Raghav Mehta and Shikha Gupta
Publication year - 2021
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst0701004
Subject(s) - cosine similarity , similarity (geometry) , recommender system , computer science , context (archaeology) , sentiment analysis , the internet , information retrieval , artificial intelligence , world wide web , machine learning , pattern recognition (psychology) , paleontology , biology , image (mathematics)
As Artificial Intelligence and Machine Learning is growing at a rapid rate over the past few years, so is theamount of data increasing exponentially on the internet. Due to this people find it difficult to choose the exactinformation they are looking for , learners find it difficult to suggest users exactly what they require. Herecomes Recommendation Systems into picture to guide users towards the information according to theirpreferences. In context of Recommendation of Movies and TV shows on Online Streaming platforms ,thispaper is aimed to explain making and implementation of Movie Recommendation Systems Using MachineLearning Algorithms, Sentiment Analysis and Cosine Similarity