Real-time Forecasting of Non-linear Competing Online Activities
Author:
Affiliation:
1. Kumamoto University, Graduate School of Science and Technology
2. Osaka University, The Institute of Scientific and Industrial Research
Publisher
Information Processing Society of Japan
Subject
General Computer Science
Link
https://www.jstage.jst.go.jp/article/ipsjjip/28/0/28_333/_pdf
Reference28 articles.
1. [1] Beutel, A., Prakash, B.A., Rosenfeld, R. and Faloutsos, C.: Interacting viruses in networks: Can both survive? KDD, pp.426-434 (2012).
2. [2] Box, G.E., Jenkins, G.M. and Reinsel, G.C.: Time Series Analysis: Forecasting and Control, Prentice Hall, Englewood Cliffs, NJ, 3rd edition (1994).
3. [3] Chakrabarti, D. and Faloutsos, C.: F4: Large-scale automated forecasting using fractals, CIKM (2002).
4. [4] Choi, H. and Varian, H.R.: Predicting the present with google trends, The Economic Record, Vol.88, No.s1, pp.2-9 (2012).
5. [5] Do, T.M., Matsubara, Y. and Sakurai, Y.: Automatic and effective mining of coevolving online activities, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (2017).
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