Research on the Application of Persona in Book Recommendation System

Abstract

Currently, there still exists a host of problems in the book recommendation system, such as low accuracy, weak correlation and poor pertinence. Aiming to unravel these problems, this paper based on the theory of big data and data mining technology, through analyzing internet user behavior and the “5C” model of personal credit evaluation, combined with joint impact weight calculation method, which involves user grade, borrowing credit, book friend recommendation degree, book friend recommended adoption degree, borrowing frequency, borrowing number, and borrowing time interval. User activity and credit are also taken into account in the process of establishing user tagging system so as to build classified book recommendation service. This method is of universal meaning to the book recommendation service of smart campus with user as the core under big data environment.