conceptual modeling

conceptual modeling

[kən′sep·chə·wəl ′mäd·liŋ]
(computer science)
Writing a program by means of which a given result will be obtained, although the result is incapable of proof. Also known as heuristic programming.
References in periodicals archive ?
In this article, we introduce conceptual modeling methods that incorporate expert ratings about a suite of properties of system components, including assessment of the state of knowledge, the strength of ecological impact, and the state of management or research attention devoted to a given component.
Computer scientists and other researchers from Europe, the US, Asia, and Kuwait address conceptual modeling, including modeling and specific languages, domain-specific conceptual modeling, and validating and communicating conceptual models; knowledge and information modeling and discovery, including knowledge representation and management, advanced data mining and analysis methods, and information recognition and modeling; linguistics modeling; cross-cultural communication and social computing; environmental modeling; and multimedia data modeling and systems, including modeling multimedia information and knowledge, content-based multimedia data management and retrieval, and privacy and context-enhancing technologies.
Keep in mind the aforementioned reasons, we considered only the concept of central dogma of molecular biology; produces sequence biological data (DNA, RNA and protein structures); to describe this reviewed study of conceptual modeling.
The formalisms developed in the field of qualitative reasoning (QR) (Forbus [2008]) can be considered natural candidates to form the basis for conceptual modeling tools, particularly as knowledge construction tools for learners (Bredeweg and Forbus 2004).
The closing chapters discuss annotation on construction documentation and the conceptual modeling environment.
Integrating the Understanding of Quality in Requirements Specification and Conceptual Modeling.
Conceptual modeling for simulation: issues and research requirements, Proceedings of the 2006 Winter Simulation Conference, IEEE, ISBN: 1-4244-05009, Piscataway, NJ
In other classification according to engineering application can divided modeling to three method, physical, mathematical and conceptual modeling.
Chapters cover the data warehouse system lifecycle, analysis and reconciliation of data sources, user requirement analysis, conceptual modeling, conceptual design, logical modeling, logical design, data-staging design, indexes for data warehouses, physical design, data warehouse project documentation, a case study, and the use of data warehouses for business intelligence.
Although I have read this article too many times to count (as probably many readers of this article have as well), when I examined it under a new lens, it occurred to me that conceptual modeling was at the very heart of this article.
They are defined to make the reuse of conceptual modeling solutions possible, using terms and jargons from the application domain [15].
This conceptual modeling methodology is dynamic and population based; that is, the risk of infection manifests at the population level.

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