Recommender system introduction for requests of cancer world

Abstract

Awareness of cancer patients and their families, health care providers, and specialized cancer centers is achieved through access to up-to-date information about various items. Today, intelligent information technology systems have an important role in the awareness of people. Therefore, a type of technology is required that is capable of learning people’s needs, interests and suggesting appropriate information accordingly. The emergence of information technology systems, like recommender systems, is a step towards selecting appropriate information. With modeling the preferences, interests, needs, requests, and behaviors of the users, recommender systems seek to predict the future preferences, needs, and behaviors of the users to recommend appropriate and helpful services accordingly. Recommender systems can be a suitable tool for the information management of cancer-related screenings, diagnoses, treatments, operations, and rehabilitation programs. Access to treatment and health recommendations from valid sources is an important component of the natural processes of human decision making. The aim of this collection is to introduce recommender systems to use in cancer-related issues.

A Neural Network-Inspired Approach for Improved and True Movie Recommendations

“…“Recommendation systems” are services that use Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques to provide the empirical solutions of the recommendations for various application frameworks and services [1]. Recommendation systems enables mobile apps and web applications to make the perception intelligently about the selection of different items, movies [2], hotels [3], food [4], tourism [5], books [6], TV shows [7], YouTube videos [8], health [9], etc. Community trends polarize towards music, movies, or videos.…”