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Scalable Uncertainty Management: 14th International Conference, SUM 2020, Bozen-Bolzano, Italy, September 2325, 2020, Proceedings 1st ed. 2020 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 297 pages, height x width: 235x155 mm, weight: 480 g, 25 Illustrations, color; 183 Illustrations, black and white; XIV, 297 p. 208 illus., 25 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 12322
  • Izdošanas datums: 03-Sep-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030584488
  • ISBN-13: 9783030584481
  • Mīkstie vāki
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  • Formāts: Paperback / softback, 297 pages, height x width: 235x155 mm, weight: 480 g, 25 Illustrations, color; 183 Illustrations, black and white; XIV, 297 p. 208 illus., 25 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 12322
  • Izdošanas datums: 03-Sep-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030584488
  • ISBN-13: 9783030584481
This book constitutes the refereed proceedings of the 14th International Conference on Scalable Uncertainty Management, SUM 2020, which was held in Bozen-Bolzano, Italy, in September 2020. The 12 full, 7 short papers presented in this volume were carefully reviewed and selected from 30 submissions. Besides that, the book also contains 2 abstracts of invited talks, 2 tutorial papers, and 2 PhD track papers. The conference aims to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as artificial intelligence and machine learning, databases, information retrieval and data mining, the semantic web and risk analysis.





Due to the Corona pandemic SUM 2020 was held as an virtual event.
Symbolic Logic Meets Machine Learning: A Brief Survey in Infinite
Domains.- Score-Based Explanations in Data Management and Machine Learning.-
From Ppossibilistic Rule-Based Systems to Machine Learning.- Logic,
Probability and Action: A Situation Calculus Perspective.- When Nominal
Analogical Proportions do not Fail.- Measuring Disagreement with
Interpolants.- Inferring from an imprecise PlackettLuce model: Application
to Label Ranking.- Inference with Choice Functions Made Practical.- A Formal
Learning Theory for Three-way Clustering.- Belief Functions for Safety
Arguments Confidence Estimation.- Incremental Elicitation of Capacities for
the Sugeno Integral with a Maximum Approach.- Computable Randomness is About
More than Probabilities.- Equity in Learning Problems: an OWA Approach.-
Conversational Recommender System by Bayesian Methods.- Dealing with Atypical
Instances in Evidential Decision-Making.- Evidence Theory Based Combination
of Frequent Chronicles for Failure Prediction.-Rule-Based Classification for
Evidential Data.- Undecided Voters as Set-Valued Information -- Towards
Forecasts under Epistemic Imprecision.- Multi-Dimensional Stable Matching
Problems in Abstract Argumentation.- Modal Interpretation of Formal Concept
Analysis for Incomplete Representations.- A Symbolic Approach for
Counterfactual Explanations.- Modelling Multivariate Ranking Functions with
Min-Sum Networks.- An Algorithm for the Contension Inconsistency Measure
using Reductions to Answer Set Programming.