Scalable Uncertainty Management [electronic resource] : 12th International Conference, SUM 2018, Milan, Italy, October 3-5, 2018, Proceedings /

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Material type: Text

TextSeries: Lecture Notes in Artificial Intelligence ; 11142Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018Description: XI, 413 p. 53 illus. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783030004613

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Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:

006.3 23

LOC classification:

Q334-342
TA347.A78

Online resources:

Click here to access online

Contents:

Answer Set Programming -- Bayesian Networks -- Data Integration -- Decision Making -- Information Theory -- Logic Programming -- Ontology -- Rank Aggregation -- Uncertainty -- Clustering -- Fuzzy logic.

In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 12th International Conference on Scalable Uncertainty Management, SUM 2018, which was held in Milan, Italy, in October 2018. The 23 full, 6 short papers and 2 tutorials presented in this volume were carefully reviewed and selected from 37 submissions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models.

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This book constitutes the refereed proceedings of the 12th International Conference on Scalable Uncertainty Management, SUM 2018, which was held in Milan, Italy, in October 2018. The 23 full, 6 short papers and 2 tutorials presented in this volume were carefully reviewed and selected from 37 submissions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models.

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