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数学中的共现单纯复形:识别知识漏洞。

Co-occurrence simplicial complexes in mathematics: identifying the holes of knowledge.

作者信息

Salnikov Vsevolod, Cassese Daniele, Lambiotte Renaud, Jones Nick S

机构信息

1University of Namur and NaXys, Rempart de la Vierge, Namur, 5000 Belgium.

2ICTEAM, University of Louvain, Av Georges Lemaître, Louvain-la-Neuve, 1348 Belgium.

出版信息

Appl Netw Sci. 2018;3(1):37. doi: 10.1007/s41109-018-0074-3. Epub 2018 Aug 28.

DOI:10.1007/s41109-018-0074-3
PMID:30839828
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6214324/
Abstract

In the last years complex networks tools contributed to provide insights on the structure of research, through the study of collaboration, citation and co-occurrence networks. The network approach focuses on pairwise relationships, often compressing multidimensional data structures and inevitably losing information. In this paper we propose for the first time a simplicial complex approach to word co-occurrences, providing a natural framework for the study of higher-order relations in the space of scientific knowledge. Using topological methods we explore the conceptual landscape of mathematical research, focusing on homological holes, regions with low connectivity in the simplicial structure. We find that homological holes are ubiquitous, which suggests that they capture some essential feature of research practice in mathematics. -dimensional holes die when every concept in the hole appears in an article together with other +1 concepts in the hole, hence their death may be a sign of the creation of new knowledge, as we show with some examples. We find a positive relation between the size of a hole and the time it takes to be closed: larger holes may represent potential for important advances in the field because they separate conceptually distant areas. We provide further description of the conceptual space by looking for the simplicial analogs of stars and explore the likelihood of edges in a star to be also part of a homological cycle. We also show that authors' conceptual entropy is positively related with their contribution to homological holes, suggesting that tend to be on the frontier of research.

摘要

在过去几年中,复杂网络工具通过对合作、引用和共现网络的研究,为洞察研究结构做出了贡献。网络方法侧重于成对关系,常常压缩多维数据结构,不可避免地会丢失信息。在本文中,我们首次提出了一种用于词共现的单纯复形方法,为研究科学知识空间中的高阶关系提供了一个自然框架。我们使用拓扑方法探索数学研究的概念景观,重点关注同调空洞,即单纯结构中连通性较低的区域。我们发现同调空洞无处不在,这表明它们捕捉到了数学研究实践的一些本质特征。当空洞中的每个概念与空洞中的其他 +1 个概念一起出现在一篇文章中时, - 维空洞就会消失,因此它们的消失可能是新知识产生的一个迹象,我们通过一些例子展示了这一点。我们发现空洞的大小与其闭合所需的时间之间存在正相关关系:较大的空洞可能代表该领域取得重要进展的潜力,因为它们分隔了概念上相距遥远的区域。我们通过寻找星的单纯类似物来进一步描述概念空间,并探索星中的边也成为同调循环一部分的可能性。我们还表明,作者的概念熵与他们对同调空洞的贡献呈正相关,这表明 往往处于研究前沿。

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