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New Technology of Library and Information Service  2015, Vol. 31 Issue (10): 2-12    DOI: 10.11925/infotech.1003-3513.2015.10.02
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Automatic Quality Evaluation of Social Tags
Zhang Chengzhi1,2, Li Lei1
1 School of Economics & Management, Nanjing University of Science and Technology, Nanjing 210094, China;
2 Jiangsu Key Laboratory of Data Engineering and Knowledge Service (Nanjing University), Nanjing 210093, China
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[Objective] It's important to improve application performance of social tags by selecting or recommending tags with high quality automatically. [Methods] The existing research on quality evaluation of social tags are separated into content and social attributes of tags, which don't combine these two attributes to evaluate the social tags. In this paper, the authors use tag's content and social attributes to evaluate the quality of tags by statistical machine learning model. [Results] Exprimental results show that with combining content and social attributes of tags, the quality evaluaton model based on SVM outperforms other models. [Limitations] Only use the blog tag data to evaluate the quality of social tags. The performance based on the social attributes are not perfect. Some social attributes can not effectively improve the automatic classification of social tags' quality. [Conclusions] This work is useful for improving the performance of the tags organization and related application.

Received: 21 July 2015      Published: 06 April 2016
:  G350  

Cite this article:

Zhang Chengzhi, Li Lei. Automatic Quality Evaluation of Social Tags. New Technology of Library and Information Service, 2015, 31(10): 2-12.

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