LEADER 01198nam a2200277 i 4500 001 991000941689707536 008 101111s2003 it 000 0 ita d 020 $a8883170113 035 $ab13935513-39ule_inst 040 $aBiblioteca Interfacoltà$bita 082 04$a027.007 245 13$aIl monaco, il libro, la biblioteca :$batti del Convegno Cassino-Montecassino, 5-8 settembre 2000 /$ca cura di Oronzo Pecere 260 $aCassino :$bEdizioni dell'Università degli studi di Cassino,$c2003 300 $a246 p. :$bill., facs. ;$c24 cm. 610 24$aMontecassino$c$xBiblioteca$vCongressi 650 4$aManoscritti liturgici$zEuropa$yMedioevo$vCongressi 650 4$aBiblioteche monastiche$vCongressi 650 4$aLibri$xStoria$yMedioevo$vCongressi 650 4$aAmanuensi$xStoria$yMedioevo$vCongressi 700 1 $aPecere, Oronzo 907 $a.b13935513$b02-04-14$c11-11-10 912 $a991000941689707536 945 $aLE002 Museo Papirologico BELT 027.009 MON$g1$i2002000618573$lle002$og$pE28.00$q-$rn$so $t0$u0$v0$w0$x0$y.i15195958$z11-11-10 996 $aMonaco, il libro, la biblioteca$9250545 997 $aUNISALENTO 998 $ale002$b11-11-10$cm$da $e-$fita$git $h3$i0 LEADER 05426nam 22006135 450 001 9910357841303321 005 20251225195126.0 010 $a3-030-35514-4 024 7 $a10.1007/978-3-030-35514-2 035 $a(CKB)4100000009939728 035 $a(DE-He213)978-3-030-35514-2 035 $a(MiAaPQ)EBC5988092 035 $a(PPN)242818447 035 $a(EXLCZ)994100000009939728 100 $a20191120d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aScalable Uncertainty Management $e13th International Conference, SUM 2019, Compiègne, France, December 16?18, 2019, Proceedings /$fedited by Nahla Ben Amor, Benjamin Quost, Martin Theobald 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XI, 452 p. 220 illus., 57 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v11940 311 08$a3-030-35513-6 327 $aAn Experimental Study on the Behaviour of Inconsistency Measures -- Inconsistency Measurement Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study -- The Hidden Elegance of Causal Interaction Models -- Computational Models for Cumulative Prospect Theory: Application to the Knapsack Problem Under Risk -- On a new evidential C-Means algorithm with instance-level constraints -- Hybrid Reasoning on a Bipolar Argumentation Framework -- Active Preference Elicitation by Bayesian Updating on Optimality Polyhedra -- Selecting Relevant Association Rules From Imperfect Data -- Evidential classification of incomplete data via imprecise relabelling: Application to plastic sorting -- An analogical interpolation method for enlarging a training dataset -- Towards a reconciliation between reasoning and learning - A position paper -- CP-nets, ?-pref nets, and Pareto dominance -- Measuring Inconsistency through Subformula Forgetting Explaining Hierarchical Multi-Linear Models -- Assertional Removed Sets Merging of DL-Lite Knowledge Bases -- An Interactive Polyhedral Approach for Multi-Objective Combinatorial Optimization with Incomplete Preference Information -- Open-Mindedness of Gradual Argumentation Semantics -- Approximate Querying on Property Graphs -- Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants -- On cautiousness and expressiveness in interval-valued logic -- Preference Elicitation with Uncertainty: Extending Regret Based Methods with Belief Functions -- Evidence Propagation and Consensus Formation in Noisy Environments -- Order-Independent Structure Learning of Multivariate Regression Chain Graphs -- l Comparison of analogy-based methods for predicting preferences -- Using Convolutional Neural Network in Cross-Domain Argumentation Mining Framework -- ConvNet and Dempster-Shafer Theory for Object Recognition -- On learning evidential contextual corrections from soft labels using a measureof discrepancy between contour functions -- Efficient Mo ?bius Transformations and their applications to D-S Theory -- From shallow to deep interactions between knowledge representation, reasoning and machine learning -- Dealing with Continuous Variables in Graphical Models -- Towards Scalable and Robust Sum-Product Networks -- Learning Models over Relational Data:A Brief Tutorial -- Subspace Clustering and Some Soft Variants -- Algebraic Approximations for Weighted Model Counting. 330 $aThis book constitutes the refereed proceedings of the 13th International Conference on Scalable Uncertainty Management, SUM 2019, which was held in Compiègne, France, in December 2019. The 25 full, 4 short, 4 tutorial, 2 invited keynote papers presented in this volume were carefully reviewed and selected from 44 submissions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v11940 606 $aArtificial intelligence 606 $aComputer science 606 $aComputer science$xMathematics 606 $aMathematical statistics 606 $aArtificial Intelligence 606 $aComputer Science Logic and Foundations of Programming 606 $aProbability and Statistics in Computer Science 615 0$aArtificial intelligence. 615 0$aComputer science. 615 0$aComputer science$xMathematics. 615 0$aMathematical statistics. 615 14$aArtificial Intelligence. 615 24$aComputer Science Logic and Foundations of Programming. 615 24$aProbability and Statistics in Computer Science. 676 $a003.54 702 $aBen Amor$b Nahla$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aQuost$b Benjamin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTheobald$b Martin$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910357841303321 996 $aScalable Uncertainty Management$9772490 997 $aUNINA