{"title":"组织人际活动知识图谱(IAKG)","authors":"Serge Sonfack Sounchio , Halguieta Trawina , Baudelaire Ismael Tankeu Nguekeu , Laurent Geneste , Bernard Kamsu-Foguem","doi":"10.1016/j.cogsys.2025.101407","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"94 ","pages":"Article 101407"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Organizations’ interpersonal activity knowledge graph (IAKG)\",\"authors\":\"Serge Sonfack Sounchio , Halguieta Trawina , Baudelaire Ismael Tankeu Nguekeu , Laurent Geneste , Bernard Kamsu-Foguem\",\"doi\":\"10.1016/j.cogsys.2025.101407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":55242,\"journal\":{\"name\":\"Cognitive Systems Research\",\"volume\":\"94 \",\"pages\":\"Article 101407\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Systems Research\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1389041725000877\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Systems Research","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389041725000877","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
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.
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.