Research On Image Mining Based On Formal Concept Analysis

Abstract

Abstract. The traditional recommendation algorithms of image tagging ignore the diversity between the visual content information and the tags recommended, which causes the recommended results have the problem of tag ambiguity, tag redundancy and so on. Therefore, this paper proposes the recommendation algorithm of image tagging based on relevance and diversity. The algorithm defines the relevance and diversity of a label set, and selects a label set which can reasonably balance the relevance and diversity to recommend to the user. The experimental results show that this algorithm improves the relevance between the recommended results and the image, and makes the recommended results be able to reflect the image content thoroughly at the same time.