Prediction in complex systems: The case of the international trade network

Alexandre Vidmer, An Zeng, Matus Medo, Yi-Cheng Zhang, Prediction in complex systems: The case of the international trade network, [Physica A 436, 188 (2015)]

简介：国家-出口品网络是一种典型的二分网，连接两类节点之间的连边表示某个国家出口了某项商品。在现有工作中，很多迭代算法能对国家的竞争力和商品的复杂程度做出估算，但至今还没有特别好的算法能对此类网络中未来连边的预测（即国家未来将出口哪些商品）。本文将一些经典的推荐算法运用到国家-出口品网络的预测中，通过用国家竞争力和商品复杂度指数对这些算法进行改进，进一步提高预测精度。此外，本文还提出了一个新的商品因果关系指数，并通过它对推荐算法进行改进，达到了最优的预测效果。

摘要

Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can be represented as a complex network where links connect countries with the products that they export. Link prediction techniques based on heat and mass diffusion processes are employed to obtain predictions for products exported in the future. These baseline predictions are improved using a recent metric of country fitness and product similarity. The overall best results are achieved with a newly developed metric of product similarity which takes advantage of causality in the network evolution.

原文链接：http://www.sciencedirect.com/science/article/pii/S0378437115004720