Online Video Platform with Context-aware Content-based Recommender System

Abstract

The problem of developing an online video platform with a context-aware content-based recommender system has been considered. Approaches to developing online video platforms have been considered. A comparison of popular online video platforms has been presented. A method of context-aware content-based recommendation of videos has been proposed. A method involves saving information about user interaction with video, obtaining and storing information about which videos the user liked, determining user context, composing a profile of user preferences, composing a profile of user preferences depending on context, determining the similarity between the video profile and a profile of user preferences (with and without context consideration), determining the relevance of the video to the context, the conclusive estimation of the relevance of the video to the user’s preferences based on the proposed composite relevance indicator. The developed structure of online video platform has been presented. The algorithm of its work has been considered. The structure of the online video platform database has been proposed. Features of designing the user interface of the online video platform have been considered. The issue of testing the developed online video platform has been considered.