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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (4): 76-83    DOI: 10.11925/infotech.2096-3467.2017.04.09
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Modeling User’s Interests Based on Image Semantics
Zeng Jin1,3, Lu Wei1,2(), Ding Heng1, Chen Haihua1
1School of Information Management, Wuhan University, Wuhan 430072, China
2Institute for Information Retrieval and Knowledge Mining, Wuhan University, Wuhan 430072, China
3School of Culture Management, Wuhan College of Media and Communications, Wuhan 430072, China
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[Objective] This paper aims to predict the user’s interests accurately with a new modeling method based on the semantics of images shared on the microblogs. [Methods] First, we crawled the image data of Sina microblogging users. Then, we used high-level semantic information from these images. Finally, we predicted user’s interests based on the image semantic classifier by the SVM training. [Results] The proposed method could predict user’s interests effectively. Among the 169 Sina microblogging users, the precision, recall and F-values were 97.38%, 98.92% and 98.14%, respectively. [Limitations] The size of the test corpus needs to be expanded to have more comprehensive results. [Conclusions] The proposed model could predict user’s interests effectively, which lays some theoretical and technical foundations for the application of high-level image semantics.

Key wordsImage Semantic      User Interest Modeling      Social Network      Support Vector Machine     
Received: 12 January 2017      Published: 24 May 2017
ZTFLH:  G353  

Cite this article:

Zeng Jin,Lu Wei,Ding Heng,Chen Haihua. Modeling User’s Interests Based on Image Semantics. Data Analysis and Knowledge Discovery, 2017, 1(4): 76-83.

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用户类别 用户总计 图像总计
旅游 42 12 530
时尚 40 11 901
动漫 37 10 751
模特 30 8 833
美食 20 5 900
总数 169 49 915
兴趣类型 P准确率 R召回率 F值
旅游 100% 100% 100%
时尚 95.56% 100% 97.73%
动漫 94.59% 94.59% 94.59%
模特 96.77% 100% 98.36%
美食 100% 100% 100%
微平均 97.17% 98.81% 97.98%
宏平均 97.38% 98.92% 98.14%
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