Design and Implementation of Comic and Animation APP Based on AR Technology
Wen Zhang, Qi Xuan · 2017
The problem of information overload is becoming more and more important in today's world. There are three kinds of methods to deal with the problem, that is, website navigation, search engine and APP. Web site navigation through the collection of well-known websites and classified ways to solve the problem of information overload. The search engine solves the problem of information overload by setting up index for massive web pages. However, when the user can not clearly express their needs, the first two on a slightly weak, and the animation class APP can solve this problem. APP animation books by analyzing the user's historical behavior records, the initiative for the user to recommend their potential content of interest. The reference of the previous animation books APP design, with personalized cartoon books APP book search engine as the goal, the research and implementation of a latent semantic analysis and fragment clustering hybrid APP scheme based on cartoon books. And the use of Hadoop large data processing framework and AR technology to solve the problem of animation books APP massive data processing. In view of the problem of the user's behavior and the variety of user's interest in the search engine, this paper proposes the latent semantic analysis model and the fragment clustering model to explore the long-term interest and immediate interest of the user behavior data.