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Titlebook: Artificial Intelligence for Knowledge Management; Third IFIP WG 12.6 I Eunika Mercier-Laurent,Danielle Boulanger Conference proceedings 201

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21#
發(fā)表于 2025-3-25 05:57:30 | 只看該作者
1868-4238 ficial Intelligence for Knowledge Management, AI4KM 2015, held in Buenos Aires, Argentina, in July 2015, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2015.?.The 9 revised and extended papers were carefully reviewed and selected from 15 submissions. They pr
22#
發(fā)表于 2025-3-25 07:37:31 | 只看該作者
23#
發(fā)表于 2025-3-25 15:32:46 | 只看該作者
Web of Data Evolution by Exploiting Agent Based-Argumentation,cular: We aim at assisting user in a such complex process. In this research work, we propose an agent based-argumentation framework to help user linked data changes. We assign for each agent a goal to acheive as process step. We rely upon communication-argumentation potential of the agent to harmonise changes with consistency.
24#
發(fā)表于 2025-3-25 17:03:12 | 只看該作者
25#
發(fā)表于 2025-3-25 22:13:04 | 只看該作者
26#
發(fā)表于 2025-3-26 02:21:50 | 只看該作者
27#
發(fā)表于 2025-3-26 06:13:16 | 只看該作者
https://doi.org/10.1057/9781137404510ake in account both ontology vocabularies and data since they should be consistent. Our general problem is to deal with web of data evolution in particular: We aim at assisting user in a such complex process. In this research work, we propose an agent based-argumentation framework to help user linke
28#
發(fā)表于 2025-3-26 11:47:07 | 只看該作者
,Human Rights and “Defamation of Religion”,versity of graphical representations and great functionality. The author focused on a characterization of free systems based on GNU GPL license which have high prospects for growth and development. The main goal of this article is to find common ground between knowledge management and content manage
29#
發(fā)表于 2025-3-26 15:34:59 | 只看該作者
30#
發(fā)表于 2025-3-26 16:49:56 | 只看該作者
Islamization and Barelvis in Pakistan,on artificial machine learning methods and a natural human learning approach. Indeed, knowledge representation with ontologies and Case-Based Reasoning (CBR) is not enough for gaining qualitative results in decision support systems. We need to manage know-how, i.e. living knowledge. For example, enh
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