Aggregating Operational Knowledge in Community Settings

Aggregating Operational Knowledge in Community Settings
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聚合社区环境中的运营知识

DOI:
10.1007/978-3-642-33615-7_23
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发表时间:
2012
期刊:
Logistics Information Management
影响因子:
--
通讯作者:
S. Srinivasa
S. Srinivasa
中科院分区:
--
文献类型:
--
作者:
S. Srinivasa

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在社区环境中,操作知识或“有用的知识”是指可以投入使用的知识要素。这可以与在人群成员之间设置背景共享心理模型的百科知识或“讲述的知识”形成对比。在任何社区中,大量的操作知识通常通过社会关系传播。虽然当今的社交媒体催化了这种传播,但它们并不主要适合捕捉和表示知识。本文认为,操作性知识聚合在某种意义上是知识聚合的对立面。后者是一个聚合的过程,将不同的局部观点聚合成一个全局观点;而前者是一个发散的过程,其中共同知识被分离成几个功利知识的局部世界。如果社区作为一个整体是一致的,这些不同的世界最终代表了社区动态的不同方面。局部世界不是相互独立的,一个局部世界的特征会影响其他局部世界的特征。为了捕捉这一现象,提出了一种称为框架上的多个世界(MWF)的数据模型,本文对此进行了详细介绍。
In a community setting, operational knowledge or “knowledge that works,” refers to knowledge elements that can be put to use. This can be contrasted with encyclopedic knowledge or “knowledge that tells” that sets the background shared mental model among members of a population. Given any community, large amounts of operational knowledge are routinely diffused through social connections. While current day social media catalyzes such diffusion, they are not primarily suited to capture and represent knowledge. This paper argues that operational knowledge aggregation is in some sense, the opposite of encyclopedic knowledge aggregation. The latter is a convergent process that aggregates different local views into a global view; while the former is a divergent process, where common knowledge gets segregated into several local worlds of utilitarian knowledge. If the community as a whole is coherent, these different worlds end up denoting different aspects of the community’s dynamics. Local worlds are not independent of one another and characteristics of one local world affect characteristics of other local worlds. To capture this phenomenon, a data model called Many Worlds on a Frame (MWF) is proposed, that is detailed in this paper.
DOI: 10.1016/j.aei.2010.05.011
发表时间: 2010-08
期刊: Adv. Eng. Informatics
影响因子: --
作者:
J. Corney;C. Torres-Sánchez;A. Jagadeesan;Xiu-Tian Yan;W. Regli;H. Medellín
通讯作者: J. Corney;C. Torres-Sánchez;A. Jagadeesan;Xiu-Tian Yan;W. Regli;H. Medellín