A Book Recommendation Algorithm Based on Improved Co-similarity Calculation

doi:10.3969/j.issn.1006-2475.2019.03.016

Abstract

Abstract: Recommendation system can solve the information overload in mass data and recommend content that users are interested in. User similarity calculation is a common recommendation algorithm, but the traditional algorithm only considers the similarity between user-item ratings and ignores the influence of users’ inherent characteristics. This paper presents an algorithm combining user feature similarity with user-item rating similarity, and uses F1 indicator to evaluate the efficiency of the recommendation algorithm. The experimental results show that the improved algorithm can effectively improve the recommendation effect.

Key words: recommended system, similarity calculation, co-similarity calculation, improved algorithm, F1 indicator

CLC Number:

TP181

LI Yue, CHEN Li, WANG Huai-bin. A Book Recommendation Algorithm Based on Improved Co-similarity Calculation[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.03.016.

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