Asocial tag clustering method based on common co-occurrence group similarity

Hui-zong LI; Xue-gang HU; Yao-jin LIN; Wei HE; Jian-han PAN

doi:10.1631/FITEE.1500187

Front. Inform. Technol. Electron. Eng ›› 2016, Vol. 17 ›› Issue (2) : 122 -134. DOI: 10.1631/FITEE.1500187

Orginal Article

Asocial tag clustering method based on common co-occurrence group similarity

Hui-zong LI ¹^,²^,^†
, Xue-gang HU ¹^,^†
, Yao-jin LIN ³^,^†
, Wei HE ¹
, Jian-han PAN ¹^,^†

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Abstract

Social tagging systems are widely applied in Web 2.0. Many users use these systems to create, organize,manage, and share Internet resources freely. However, many ambiguous and uncontrolled tags produced by social tagging systems not only worsen users’ experience, but also restrict resources’ retrieval efficiency. Tag clustering can aggregate tags with similar semantics together, and help mitigate the above problems. In this paper, we first present a common co-occurrence group similarity based approach, which employs the ternary relation among users,resources, and tags to measure the semantic relevance between tags. Then we propose a spectral clustering method to address the high dimensionality and sparsity of the annotating data. Finally, experimental results show that the proposed method is useful and efficient.

Keywords

Social tagging systems / Tag co-occurrence / Spectral clustering / Group similarity http://dx.doi.org/10.1631/FITEE.1500187

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Hui-zong LI, Xue-gang HU, Yao-jin LIN, Wei HE, Jian-han PAN. Asocial tag clustering method based on common co-occurrence group similarity. Front. Inform. Technol. Electron. Eng, 2016, 17(2): 122-134 DOI:10.1631/FITEE.1500187

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