Research On Image Mining Based On Formal Concept Analysis

DOI

10.2991/iiicec-15.2015.11How to use a DOI?

Keywords

Soccer Robot; Mechanical Analysis; Optimal Design

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - ZhiHua Zeng
AU  - Bing Zhou
AU  - Cong Li
PY  - 2015/03
DA  - 2015/03
TI  - Research On Image Mining Based On Formal Concept Analysis
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 44
EP  - 47
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.11
DO  - 10.2991/iiicec-15.2015.11
ID  - Zeng2015/03
ER  -