Name
Abstract | ||
|---|---|---|
Creative knowledge discovery—finding useful, previously unknown links between concepts—is a vital tool in unlocking the economic and social value of the vast range of networked data and services that is now available. We define “standard” knowledge discovery as the search for explanatory and predictive patterns in a specific domain, usually with a large volume of data. In contrast, creative knowledge discovery is concerned with the creation of new (and effective) patterns—either by generalization of existing patterns or by analogy to patterns in other domains. An important precondition for creative knowledge discovery is that we understand the relations within the data. Fuzzy formal concept analysis is a powerful approach that enables us to find embedded structure in data and to extract novel concepts that can be used in subsequent processing such as creative knowledge discovery. This paper outlines a fast algorithm for computing fuzzy formal concepts and provides a brief illustration of the use of fuzzy formal concept analysis in creative knowledge discovery. © 2013 Wiley Periodicals, Inc. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1002/int.21576 | Int. J. Intell. Syst. |
Keywords | Field | DocType |
brief illustration,finding fuzzy concepts,wiley periodicals,knowledge discovery,creative knowledge discovery,embedded structure,fuzzy formal concept analysis,fast algorithm,fuzzy formal concept,networked data,novel concept | Data science,Fuzzy formal concept analysis,Computer science,Fuzzy logic,Precondition,Artificial intelligence,Knowledge extraction,Analogy | Journal |
Volume | Issue | ISSN |
28 | 1 | 0884-8173 |
Citations | PageRank | References |
7 | 0.55 | 16 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Trevor Martin | 1 | 45 | 5.66 |
| Andrei Majidian | 2 | 25 | 2.98 |