Abstract
We address the problem of estimating the expected influence curves with good accuracy from a single observed information diffusion sequence, for both the asynchronous independent cascade (AsIC) model and the asynchronous linear threshold (AsLT) model. We solve this problem by first learning the model parameters and then estimating the influence curve using the learned model. Since the length of the observed diffusion sequence may vary from a very long one to a very short one, we evaluate the proposed method by simulation using artificial diffusion sequence of various lengths and show that the proposed method can estimate the expected influence curve robustly from a single diffusion sequence with various lengths.
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Yoshikawa, Y., Saito, K., Motoda, H., Ohara, K., Kimura, M. (2010). Acquiring Expected Influence Curve from Single Diffusion Sequence. In: Kang, BH., Richards, D. (eds) Knowledge Management and Acquisition for Smart Systems and Services. PKAW 2010. Lecture Notes in Computer Science(), vol 6232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15037-1_23
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DOI: https://doi.org/10.1007/978-3-642-15037-1_23
Publisher Name: Springer, Berlin, Heidelberg
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