Extracting Fuzzy Linguistic Summaries Based on Including Degree Theory and FCA View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2007

AUTHORS

Li Zhang , Zheng Pei , Honghua Chen

ABSTRACT

In information systems (or database), generally, attribute values of objects are numeral or symbols, from application point of view, linguistic information or decision rules are widely used. Hence, fuzzy linguistic summaries would be very desirable and human consistent. In this paper, extracting fuzzy linguistic summaries from a continuous information system is discussed. Due to fuzzy linguistic summaries can not be extracted directly in the information system, fuzzy information system is used to discretize the continuous information system, and level cut set is used to obtain classical information system firstly. Then based on including degree theory and formal concept analysis (FCA), simple fuzzy linguistic summaries are extracted. To extract complex linguistic summaries, logical conjunctions ∨ , ∧ and → are used. An Example of checking quality of sweetened full cream milk powder is also provided. More... »

PAGES

273-283

Book

TITLE

Foundations of Fuzzy Logic and Soft Computing

ISBN

978-3-540-72917-4
978-3-540-72950-1

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-72950-1_28

DOI

http://dx.doi.org/10.1007/978-3-540-72950-1_28

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1051251555


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