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Scalable Uncertainty Management : 8th International Conference, SUM 2014, Oxford, UK, September 15-17, 2014, Proceedings / edited by Umberto Straccia, Andrea Cali.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Straccia, Umberto, Editor.
Calì, Andrea, Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 8720
Lecture Notes in Artificial Intelligence, 2945-9141 ; 8720
Language:
English
Subjects (All):
Artificial intelligence.
Application software.
Information storage and retrieval systems.
Computer networks.
Database management.
Data mining.
Artificial Intelligence.
Computer and Information Systems Applications.
Information Storage and Retrieval.
Computer Communication Networks.
Database Management.
Data Mining and Knowledge Discovery.
Local Subjects:
Artificial Intelligence.
Computer and Information Systems Applications.
Information Storage and Retrieval.
Computer Communication Networks.
Database Management.
Data Mining and Knowledge Discovery.
Physical Description:
1 online resource (X, 322 pages) : 45 illustrations
Edition:
1st ed. 2014.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2014.
System Details:
text file PDF
Summary:
This book constitutes the refereed proceedings of the 8th International Conference on Scalable Uncertainty Management, SUM 2014, held in Oxford, UK, in September 2014. The 20 revised full papers and 6 revised short papers were carefully reviewed and selected from 47 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.
Contents:
Possibilistic networks: A new setting for modeling preferences
Min-based assertional merging approach for possibilistic DL-Lite knowledge bases
On the revision of possibilistic DL-Lite knowledge bases
Interval-based possibilistic networks
Tractable vs. Intractable Cases of Query Answering under Matching Dependencies
Analogical classification: Handling numerical data
Lazy Analogical Classification: Optimization and Precision Issues
Update Operators for Inconsistent Query Answering: A New Point of View
Improving Inconsistency Resolution by Considering Global Conflicts
Probabilistic Argumentation Frameworks - A Logical Approach
Computing Skyline from Evidential Data
A Two-Level Approach to Maximum Entropy Model Computation for Relational Probabilistic Logic Based on Weighted Conditional Impacts: Solving Hidden-Semi-Markov-Mode Markov Decision Problems
Probabilistic Strategies in Dialogical Argumentation
Analytics over Probabilistic Unmerged Duplicates
Answering Ontological Ranking Queries based on Subjective Reports
A Petri net model of argumentation dynamics
Integrity Constraints for Probabilistic Spatio-Temporal Knowledgebases.
Other Format:
Printed edition:
ISBN:
978-3-319-11508-5
9783319115085
Access Restriction:
Restricted for use by site license.

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