Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.
PLoS One. 2010 Dec 2;5(12):e14139. doi: 10.1371/journal.pone.0014139.
Zipf's law and Heaps' law are observed in disparate complex systems. Of particular interests, these two laws often appear together. Many theoretical models and analyses are performed to understand their co-occurrence in real systems, but it still lacks a clear picture about their relation.
METHODOLOGY/PRINCIPAL FINDINGS: We show that the Heaps' law can be considered as a derivative phenomenon if the system obeys the Zipf's law. Furthermore, we refine the known approximate solution of the Heaps' exponent provided the Zipf's exponent. We show that the approximate solution is indeed an asymptotic solution for infinite systems, while in the finite-size system the Heaps' exponent is sensitive to the system size. Extensive empirical analysis on tens of disparate systems demonstrates that our refined results can better capture the relation between the Zipf's and Heaps' exponents.
CONCLUSIONS/SIGNIFICANCE: The present analysis provides a clear picture about the relation between the Zipf's law and Heaps' law without the help of any specific stochastic model, namely the Heaps' law is indeed a derivative phenomenon from the Zipf's law. The presented numerical method gives considerably better estimation of the Heaps' exponent given the Zipf's exponent and the system size. Our analysis provides some insights and implications of real complex systems. For example, one can naturally obtained a better explanation of the accelerated growth of scale-free networks.
齐夫定律和赫普定律在不同的复杂系统中都有体现。特别值得关注的是,这两个定律经常同时出现。许多理论模型和分析被用来理解它们在真实系统中的共同出现,但它们之间的关系仍然缺乏清晰的认识。
方法/主要发现:我们表明,如果系统遵守齐夫定律,那么赫普定律可以被视为衍生现象。此外,我们还细化了已知的赫普指数的近似解,给出了齐夫指数。我们表明,该近似解确实是无限系统的渐近解,而在有限大小的系统中,赫普指数对系统大小敏感。对数十个不同系统的广泛实证分析表明,我们的改进结果可以更好地捕捉齐夫定律和赫普定律之间的关系。
结论/意义:本分析在没有任何特定随机模型帮助的情况下,提供了齐夫定律和赫普定律之间关系的清晰认识,即赫普定律确实是齐夫定律的衍生现象。所提出的数值方法在给定齐夫指数和系统大小的情况下,能够更好地估计赫普指数。我们的分析为真实复杂系统提供了一些见解和启示。例如,人们可以自然地对无标度网络的加速增长给出更好的解释。