Methodology for Multi-Aspect Ontology Development: Ontology for Decision Support Based on Human-Machine Collective Intelligence

被引:6
|
作者
Smirnov, Alexander [1 ]
Levashova, Tatiana [1 ]
Ponomarev, Andrew [1 ]
Shilov, Nikolay [1 ]
机构
[1] Russian Acad Sci, St Petersburg Fed Res Ctr, St Petersburg 199178, Russia
来源
IEEE ACCESS | 2021年 / 9卷 / 09期
基金
俄罗斯科学基金会;
关键词
Ontologies; Collective intelligence; Decision support systems; Man-machine systems; Spread spectrum communication; Software; Interoperability; Ontology development methodology; multi-aspect ontology; collective intelligence; human-computer teamwork; decision support system;
D O I
10.1109/ACCESS.2021.3116870
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The advantage of human-machine collective intelligence for decision support systems is the ability to make better decisions due to the mitigation of human biases in the generation of potential solutions and their evaluation. So far, the potential of human-machine collective intelligence was used only in few decision support systems, however, teamwork between humans and machines has not been achieved. This is partly due to the lack of interoperability in these systems. In earlier works, the authors proposed the apparatus of multi-aspect ontologies implying the integration of multiple domain ontologies to provide interoperability between humans and machines and coordinate interrelated processes going on in the systems of the considered type. Such ontologies have proved efficient for systems that require intensive information and knowledge exchange between loosely-related dynamic autonomous domains (e.g., enterprise knowledge management, product lifecycle management, or human-machine collective intelligence systems). However, existing ontology development methodologies fail to recommend a process that would support cross-domain knowledge integration during the multi-aspect ontology development. Moreover, the structure of the multi-aspect ontology imposes some restrictions on the integration approach. The paper proposes such a methodology for the multi-aspect ontology development that incorporates the aspect integration approach at multiple levels. The methodology is applied to develop a multi-aspect ontology for decision support based on human-machine collective intelligence. An example from the "e-tourism" domain demonstrates the applicability of the proposed methodology as well as the usage of the multi-aspect ontology for a human-machine environment aimed at solving real-world problems. The proposed methodology can facilitate the development of ontologies for complex knowledge-based systems that operate with knowledge from multiple loosely-connected domains.
引用
收藏
页码:135167 / 135185
页数:19
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