组织人际活动知识图谱(IAKG)

IF 2.4 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Serge Sonfack Sounchio , Halguieta Trawina , Baudelaire Ismael Tankeu Nguekeu , Laurent Geneste , Bernard Kamsu-Foguem
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引用次数: 0

摘要

今天的知识支持组织的成长,让他们保持竞争力,并使他们能够设计新的产品和服务或做出有效的决策。这种知识分为两种主要形式:显性知识,易于编码、存储和访问;隐性知识,员工拥有关于产品、服务以及他们如何执行组织活动的知识。与显性知识不同,隐性知识,特别是组织的个人活动知识,在获取、形式化和重用方面具有挑战性。此外,以人为中心的个人知识图方法不适合用于个人活动知识的表示和推理。一方面,本研究描述和描述了以人为中心的个人知识图方法在组织内表示个人活动知识的局限性。然后,从社会科学中确立的活动理论概念的延伸出发,阐述了个人活动本体论。所建议的框架支持组织内个人活动知识的捕获、形式化、共享和推理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Organizations’ interpersonal activity knowledge graph (IAKG)
Knowledge today supports organizations’ growth, lets them stay competitive, and enables them to design new products and services or make effective decisions. This knowledge is classified into two primary forms: explicit knowledge, which is easy to encode, store, and access, and implicit knowledge, which employees possess regarding products, services, and how they carry out an organization’s activities. Unlike explicit knowledge, implicit knowledge, and particularly organizations’ personal activity knowledge, is challenging to capture, formalize, and reuse. Moreover, the human-centered personal knowledge graph approach is unfit for the personal activity knowledge representation and reasoning. On the one hand, this study describes and depicts the limitations of human-centered personal knowledge graph approaches for representing personal activity knowledge within an organization. Afterward, it elaborates on a personal activity ontology derived from an extension of the activity theory concept established in social sciences. The proposed framework enables the capture, formalization, sharing, and reasoning of personal activity knowledge within an organization.
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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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