Using linguistic summaries and concepts for understanding large data. (November 2016)

• Record Type: Journal Article
• Authors: Yager, Ronald R.; Yager, Rachel L.
• Is Part Of: Engineering applications of artificial intelligence. Volume 56(2016:Aug.)
• Page Start: 273
• Page End: 280
• Publication Date: 2016-11
• Subjects: Summarization -- Linguistic Summaries -- Concept Formation -- Aggregation -- Data Mining; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2016.09.009
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: We introduce the basic ideas of linguistic summaries. We describe the validation of the summary based upon the compatibility of the data and linguistic terms used in the summary. We next discuss the idea of concepts and describe how to build these concepts from an aggregation of constituent concepts. We discuss the role that hierarchies play in formulating rich concepts. We show how to include these concepts in linguistic summaries and in particular how to validate a summary that contains concepts. We look at the role of aggregation operators in the construction of the rich concepts. We explain how to build concepts using the OWA aggregation operator. Finally we discuss the use of the Choquet integral as means of building rich concepts.