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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (3): 49-59    DOI: 10.11925/infotech.2096-3467.2017.1023
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Recommending Image Based on Feature Matching
Liu Dongsu, Huo Chenhui()
School of Economics and Management, Xidian University, Xi’an 710071, China
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[Objective] This paper developed an image recommendation model based on feature matching technique and the LSH algorithm, aiming to improve the accuracy of recommendations. [Methods] First, we extracted the image’s SIFT features as the matching criteria. Then, we modified the LSH algorithm to retrieve images in high dimensional settings. Finally, we proposed an ICF-LSH algorithm based on the collaborative filtering techniques to build fusion recommendation model. [Results] We examined the proposed algorithm with various datasets and achieved better recall and precision rates for image recommendation. [Limitations] Only used the SIFT feature to extract image features. More research is needed to explore other matching features. [Conclusions] The proposed model improves the performance of image matching and recommendation systems.

Key wordsSIFT Feature      LSH      Image Matching      Recommendation System     
Received: 13 October 2017      Published: 03 April 2018
ZTFLH:  N99 TP391  

Cite this article:

Liu Dongsu,Huo Chenhui. Recommending Image Based on Feature Matching. Data Analysis and Knowledge Discovery, 2018, 2(3): 49-59.

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数据集大小 召回率 错误率 匹配耗时(s) Hash表长度
2 000 0.82 1.421 0.042 12
4 000 0.90 1.337 0.069 19
6 000 0.93 1.223 0.085 34
8 000 0.96 1.069 0.126 47
数据集大小 召回率 错误率 匹配耗时(s) Hash表长度
2 000 0.41 5.913 0.142 25
4 000 0.50 5.673 0.278 39
6 000 0.64 4.825 0.455 49
8 000 0.77 4.546 0.724 61
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