Portmann, Edy; Kaltenrieder, Patrick; Pedrycz, Witold (2015). Knowledge representation through graphs. Procedia Computer Science, 62, pp. 245-248. Elsevier 10.1016/j.procs.2015.08.446
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Due to the increasing amount of data, knowledge aggregation, representation and reasoning are highly important for companies. In this paper, knowledge aggregation is presented as the first step. In the sequel, successful knowledge representation, for instance through graphs, enables knowledge-based reasoning. There exist various forms of knowledge representation through graphs; some of which allow to handle uncertainty and imprecision by invoking the technology of fuzzy sets. The paper provides an overview of different types of graphs stressing their relationships and their essential features.
Item Type: |
Conference or Workshop Item (Paper) |
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Division/Institute: |
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Management 03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems |
UniBE Contributor: |
Portmann, Edy, Kaltenrieder, Patrick |
Subjects: |
000 Computer science, knowledge & systems 600 Technology > 650 Management & public relations 300 Social sciences, sociology & anthropology > 330 Economics |
ISSN: |
1877-0509 |
Publisher: |
Elsevier |
Projects: |
[388] Knowledge Aggregation, Representation and Reasoning |
Language: |
English |
Submitter: |
Sara D'Onofrio |
Date Deposited: |
08 Jan 2015 15:14 |
Last Modified: |
05 Dec 2022 14:38 |
Publisher DOI: |
10.1016/j.procs.2015.08.446 |
BORIS DOI: |
10.7892/boris.61468 |
URI: |
https://boris.unibe.ch/id/eprint/61468 |
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