سیویلیکا را در شبکه های اجتماعی دنبال نمایید.

Artificial intelligence in recommender systems

Publish Year: 1403
Type: Conference paper
Language: English
View: 84

This Paper With 7 Page And PDF Format Ready To Download

این Paper در بخشهای موضوعی زیر دسته بندی شده است:

Export:

Link to this Paper:

Document National Code:

CONFIT01_0873

Index date: 25 September 2024

Artificial intelligence in recommender systems abstract

Artificial Intelligence (AI) is a modern engineering method to make machines think or use their intelligence like humans by mimicking traits and by learning to take appropriate decisions and to perform assigned tasks properly. Some of the companies which have done remarkable work in the field of Artificial Intelligence (AI) are Facebook, Google, Microsoft, IBM, etc. which are investing millions and billions in this very field of AI development and research. Currently there is a huge market and need for building Intelligent Systems for Recommendation. To counter this, one of the easiest and most preferable System is Recommendation System (RS). Recommendation Systems had proved to play an important role in the field of E-Commerce websites, Online Shopping, Dating Apps, Social-Networking, Digital Marketing, Online Advertisements, etc. by providing personalized recommends and feedback to users according to their preferences and choices. Artificial intelligence plays a key role in recommender systems by enabling the algorithms to learn from user interactions and adapt to changing preferences over time. Machine learning techniques such as deep learning and natural language processing are often used to improve the accuracy and effectiveness of recommender systems. Overall, artificial intelligence in recommender systems helps businesses increase customer engagement, drive sales, and enhance user experience by providing personalized recommendations that are tailored to each individual user's preferences and interests.

Artificial intelligence in recommender systems Keywords:

Artificial intelligence in recommender systems authors

Vahid Mirzaei

process control bachelor's degree / University of Applied Science and Technology