Abstract
In recent years, folksonomy becomes a hot topic in many research fields such as complex systems, information retrieval, and recommending systems. It is essential to study the semantic relationships among tags in folksonomy applications. The main contributions of this paper includes: (a) proposes a general framework for the analysis of the semantic relationships among tags based on their co-occurrence. (b)investigates eight correlation measurements from various fields; then appliying these measurements to searching similar tags for a given tag on datasets from del.icio.us. (c) conducts a comparative study on both accuracy and time performance of the eight measurements. From the comparison, a best overall correlation measurement is concluded for similar tags searching in the applications of folksonomy.
Supported by the 11th Five Years Key Programs for Sci. &Tech. Development of China under grant No. 2006BAI05A01, the National Science Foundation under grant No 60773169, the Software Innovation Project of Sichuan Youth under Grant No 2007AA0155 and the Development Foundation of Chengdu Univeristy of Information Technology(KYTZ200811).
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Xu, K., Chen, Y., Jiang, Y., Tang, R., Liu, Y., Gong, J. (2008). A Comparative Study of Correlation Measurements for Searching Similar Tags. In: Tang, C., Ling, C.X., Zhou, X., Cercone, N.J., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2008. Lecture Notes in Computer Science(), vol 5139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88192-6_75
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DOI: https://doi.org/10.1007/978-3-540-88192-6_75
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