Research on data mining and the short video platforms users' personalized information needs

Abstract

The popularization and development of the Internet has prompted people to enter the era of informatization and digitization. With the development of new media technology and the influx of massive amounts of information, the problem between human information needs and information has changed from insufficient information to "useful" information acquisition difficulties. As a form of new media, short video has been favored by many people because of its unique characteristics since its emergence, but if the short video platform wants to get healthy and sustainable development, it needs to meet the personalized information needs of users to the greatest extent. At this time, the acquisition and analysis of users' personalized needs has become one of the focuses of the platform's work. Taking the short video platform as an example, this paper uses the K-means clustering analysis algorithm in data mining and the Apriori association rule mining algorithm to analyze the user's personalized information needs, and then according to the users requirements analysis, a user personalized information recommendation system for short video platforms - "KA-R" system is proposed to meet the purpose of meeting the personalized information needs of users.