在线网络中的趋势预测
来源:作者:曾安 发布时间:2016-06-08 浏览次数:621
Predicting the
future trend of popularity by network diffusion
An
Zeng and Chi Ho Yeung
[Chaos
26, 063102 (2016);]
http://dx.doi.org/10.1063/1.4953013
在线网络中的趋势预测
从在线网络中预测出未来流行的商品在实际问题中有着重要的应用价值。传统方法主要基于商品已有流行性的线性外推方法来进行预测。这种方法在预测短期流行性方面有比较高的精确度,但在预测长期趋势时效果不佳。本文提出了一种基于用户-商品二分网上的扩散过程来做趋势预测。这种方法能够通过网络中微观层面的连边信息来预测商品的宏观行为。我们将这个方法运用在Netflix和Amazon这样的在线商务网络中,和美国物理学会引文网络中。结果显示我们的方法能够比线性外推法更准确的定位出小度商品中有潜力的商品(即未来将变得流行的商品)。
摘要:
Conventional
approaches to predict the future popularity of products are mainly based on extrapolation
of their current popularity, which overlooks the hidden microscopic information
under the macroscopic trend. Here, we study diffusion processes on consumer-product
and citation networks to exploit the hidden microscopic information and connect
consumers to their potential purchase, publications to their potential citers
to obtain a prediction for future item popularity. By using the data obtained
from the largest online retailers including Netflix and Amazon as well as the
American Physical Society citation networks, we found that our method
outperforms the accurate short-term extrapolation and identifies the
potentially popular items long before they become prominent.