Personalized movie recommendations based on probabilistic linguistic sentiment and integrated DEMATEL-TODIM methods.

ABSTRACT: With the development of society, online reviews are increasingly becoming a crucial factor in decision-making. Especially for entertainment products such as movies, they are preferred for their affordability and high entertainment factor. Therefore, this paper proposes a movie recommendation model that considers user personalization using a probabilistic linguistic approach based on online reviews. Firstly, the method constructs a quantitative sentiment framework that transforms comments into a multi-granular probabilistic sentiment language. Secondly, we build the decision-making trial and evaluation laboratory (DEMATEL) method for probabilistic linguistic environments to explore interrelationships between product attributes, and improve the distance measure and score function to better i

SUBMITTER: Wang Q 

PROVIDER: S-EPMC11349909 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature