Abstract
This paper study temporal curve patterns associated with BBS information and how the information’s popularity grows and fades over time. We develop the Temporal-Peak clustering algorithm that accurately finds the curve pattern in BBS. According to the characteristics of BBS platform and applying sudden and durative describes temporal variation curve of information. The article demonstrates our approach on a massive dataset. The algorithm effectively avoids interference of random in the temporal node. Temporal-Peak accurately and succinctly finds temporal curve patterns in BBS.
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Yu, Y., Hu, Y., Li, G. (2014). Temporal Curve Patterns Discovery of Information in BBS. In: Han, W., Huang, Z., Hu, C., Zhang, H., Guo, L. (eds) Web Technologies and Applications. APWeb 2014. Lecture Notes in Computer Science, vol 8710. Springer, Cham. https://doi.org/10.1007/978-3-319-11119-3_5
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DOI: https://doi.org/10.1007/978-3-319-11119-3_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11118-6
Online ISBN: 978-3-319-11119-3
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