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Localising iceberg inconsistencies

Glauber De Bona, Anthony Hunter
2017 Artificial Intelligence  
In artificial intelligence, it is important to handle and analyse inconsistency in knowledge bases. Inconsistent pieces of information suggest questions like "where is the inconsistency?"  ...  We apply the framework presented to the problem of measuring inconsistency in knowledge bases, putting forward relaxed forms for two debatable postulates for inconsistency measures.  ...  Acknowledgements GDB is supported by CNPq grant PDE 200780/2015-8. AH is partly supported by EPSRC grant EP/N008294/1.  ... 
doi:10.1016/j.artint.2017.02.005 fatcat:yyvxibp7tfa6fn6qyfrcazqypi

Knowledge Engineering for Intelligent Decision Support

María Vanina Martínez
2017 Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence  
Knowledge can be seen as the collection of skills and information an individual (or group) has acquired through experience, while intelligence as the ability to apply such knowledge.  ...  From my point of view, an AI should be able to combine automatically acquired data and knowledge together with specific domain expertise from the users that the tool is expected to help.  ...  with Legal texts, and by funds provided by CONICET, Dep. de Ciencias e Ing. de la Computacin, Universidad Nacional del Sur, and Agencia Nacional de Promoción Científica y Tecnológica, Argentina.  ... 
doi:10.24963/ijcai.2017/736 dblp:conf/ijcai/Martinez17 fatcat:cgxriw3cs5cjhaciauodhjptse

Handling Revision Inconsistencies: Creating Useful Explanations

Fabian Schmidt, Jorg Gebhardt, Rudolf Kruse
2015 2015 48th Hawaii International Conference on System Sciences  
With ever growing knowledge bases the presence of inconsistencies has become a major challenge.  ...  In the past mainly the problems of finding and removing inconsistencies from knowledge bases have been addressed.  ...  Revision is a belief change operation that transfers a given prior knowledge base into a posterior knowledge base while respecting the principle of minimal change.  ... 
doi:10.1109/hicss.2015.447 dblp:conf/hicss/SchmidtGK15 fatcat:un4irznuo5cjfcd7fxunmauawu

The Tweety Library Collection for Logical Aspects of Artificial Intelligence and Knowledge Representation

Matthias Thimm
2016 Künstliche Intelligenz  
Finally, this thesis addresses the implementation challenges for various kinds of knowledge representation formalisms employing any notion of inconsistency tolerance or uncertainty. iii P U B L I C AT  ...  A B S T R A C T This habilitation thesis collects works addressing several challenges on handling uncertainty and inconsistency in knowledge representation.  ...  Conditional Logic The Conditional Logic library extends the Propositional Logic library by conditionals, i. e., non-classical rules of the form (B | A) ("A usually implies B"), cf.  ... 
doi:10.1007/s13218-016-0458-4 fatcat:wp6lphcwevhd3p3mrolv2masku

Page 9558 of Mathematical Reviews Vol. , Issue 2003m [page]

2003 Mathematical Reviews  
Next, we define resource-bounded consolidation operations that limit and control the generation of maximal consistent subsets of a stratified knowledge base.  ...  In this issue, a number of authors have explored the idea of reasoning with maximal consistent subsets of an inconsistent stratified knowl- edge base.  ... 

Belief Base Revision for Datalog+/- Ontologies [chapter]

Songxin Wang, Jeff Z. Pan, Yuting Zhao, Wei Li, Songqiao Han, Dongmei Han
2014 Lecture Notes in Computer Science  
Finally, we give the complexity results by showing that query answering for a revised linear Datalog+/-ontology is tractable.  ...  Datalog+/-is a family of emerging ontology languages that can be used for representing and reasoning over lightweight ontologies in Semantic Web.  ...  This work is partially supported by the National Natural Science Foundation of China Grant No.61003022 and Grant No.41174007, as well as the FP7 K-Drive project (No. 286348) and the EPSRC WhatIf project  ... 
doi:10.1007/978-3-319-14122-0_14 fatcat:bt6q5frxyvhsjpfh3uamx2y6qy

Belief Base Revision for Datalog+/- Ontologies [chapter]

Songxin Wang, Jeff Z. Pan, Yuting Zhao, Wei Li, Songqiao Han, Dongmei Han
2014 Lecture Notes in Computer Science  
Finally, we give the complexity results by showing that query answering for a revised linear Datalog+/-ontology is tractable.  ...  Datalog+/-is a family of emerging ontology languages that can be used for representing and reasoning over lightweight ontologies in Semantic Web.  ...  This work is partially supported by the National Natural Science Foundation of China Grant No.61003022 and Grant No.41174007, as well as the FP7 K-Drive project (No. 286348) and the EPSRC WhatIf project  ... 
doi:10.1007/978-3-319-06826-8_14 fatcat:ayqivf5zwfbnncbnudyj4ocjsi

A L1 Minimization Optimal Corrective Explanation Procedure for Probabilistic Databases [chapter]

Marco Baioletti, Andrea Capotorti
2020 Communications in Computer and Information Science  
Supported by project "Algebraic statistics in a coherent setting for Bayesian networks" -DMI Unipg -Ricerca di Base 2018.  ...  We propose to use a, recently introduced, efficient L1 distance minimization through mixed-integer linear programming for minimizing the number of valuations to be modified inside an incoherent probabilistic  ...  The knowledge of all the bi-optimal corrective explanations permits the decision maker to select the most appropriate adjustment of an inconsistent probabilistic database.  ... 
doi:10.1007/978-3-030-50146-4_7 fatcat:vhpcmrqu7vhrdgqadfioxufgvm

Probabilistic Reasoning with Abstract Argumentation Frameworks

Anthony Hunter, Matthias Thimm
2017 The Journal of Artificial Intelligence Research  
We generalise this scenario by also considering inconsistent assessments, i.e., assessments that contradict the topology of the argumentation framework.  ...  of the argumentation framework and principles of probabilistic reasoning into account.  ...  Acknowledgements We thank Sylwia Polberg for making us aware of an erroneous result in a previous version of this paper.  ... 
doi:10.1613/jair.5393 fatcat:krgtiksxnbetfjiobzfdufirhq

Bayesian Reasoning Over Models

Sebastian J. I. Herzig, Christiaan J. J. Paredis
2014 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems  
While the commonly employed rule-based approaches to identifying inconsistencies can be effective, state of the art methods for inferring or determining semantic overlaps are not.  ...  A crucial part of verifying and validating models is the identification of inconsistencies. Inconsistencies can exist whenever models overlap semantically.  ...  This work was supported by Boeing Research & Technology. The authors would like to thank Michael Christian (The Boeing Company), Dr.  ... 
dblp:conf/models/HerzigP14 fatcat:z5gm5hssnfdknluqfe44rmajny

Assessment of Overhaul Effectiveness and Usage-based Inference using Bayesian Networks

Nenad G. Nenadic, Christopher J. Valant, Sean P. McConky, Michael G. Thurston
2018 Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM  
The first method employs a probabilistic model to reconcile missing and inconsistent data entries; the second is based on the replacement of consumable components.  ...  The probabilistic model, fully and uniquely specified by the probabilistic variables (with their distributions) and deterministic variables, is validated using synthetic datasets because the real ground  ...  Consolidation of vehicle fleet data in a data warehouse provides an opportunity to develop PHM knowledge and algorithms incrementally.  ... 
doi:10.36001/phmconf.2018.v10i1.295 fatcat:5fhfklughbdqnmigh3migsgjgi

Ontology Design for Scientific Theories That Make Probabilistic Predictions

David Poole, Clinton Smyth, Rita Sharma
2009 IEEE Intelligent Systems  
A multidimensional ontology design paradigm based on Aristotelian definitions provides knowledge structure necessary for testing scientific theories that make probabilistic predictions.  ...  Through the use of axioms, the system should be able to infer some implicit knowledge or determine that some combination of values is inconsistent.  ...  He's known for his work on knowledge representation, default reasoning, assumption-based reasoning, diagnosis, reasoning under uncertainty, combining logic and probability, algorithms for probabilistic  ... 
doi:10.1109/mis.2009.15 fatcat:k73dih5oo5dq3op3xxxfqt4a4e

Class-distribution regularized consensus maximization for alleviating overfitting in model combination

Sihong Xie, Jing Gao, Wei Fan, Deepak Turaga, Philip S. Yu
2014 Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '14  
Various methods have been proposed to combine predictions such that the final predictions are maximally agreed upon by multiple base models.  ...  In data mining applications such as crowdsourcing and privacypreserving data mining, one may wish to obtain consolidated predictions out of multiple models without access to features of the data.  ...  Acknowledgements This work is supported in part by China 973 Fundamental R&D Program (No.2014CB340304), NSF grants (CNS-1115234, DBI-0960443, OISE-1129076, and IIS-1319973) and Huawei grant.  ... 
doi:10.1145/2623330.2623676 dblp:conf/kdd/XieGFTY14 fatcat:vzsbe5oybralfnekbg5snhaxwy

A Probabilistic Logic of Cyber Deception

Sushil Jajodia, Noseong Park, Fabio Pierazzi, Andrea Pugliese, Edoardo Serra, Gerardo I. Simari, V. S. Subrahmanian
2017 IEEE Transactions on Information Forensics and Security  
We propose a Probabilistic Logic of Deception (PLD-Logic) and show that various computations are NP-hard. We model the attacker's state and show the effects of faked scan results.  ...  We ran detailed experiments to assess the performance of these algorithms and further show that by running Fast-PLD offline and storing the results, we can very efficiently answer run-time scan requests  ...  expressed in this material are those of the authors and do not necessarily reflect the views of the ONR), by MIUR grant PON03PE 00032 2, by EU H2020 research and innovation program under the Marie Sklodowska-Curie  ... 
doi:10.1109/tifs.2017.2710945 fatcat:fmcmx5w6w5bthamuh4s56puoqy

Edit Constraints on Microaggregation and Additive Noise [chapter]

Isaac Cano, Vicenç Torra
2011 Lecture Notes in Computer Science  
We check its suitability against the constrained microaggregation, a method for microaggregation that avoid the introduction of such inconsistencies.  ...  Such perturbation can introduce inconsistencies to the sensitive data.  ...  Acknowledgments Partial support by the Spanish MICINN (projects eAEGIS TSI2007-65406-C03-02, ARES -CONSOLIDER INGENIO 2010 CSD2007-00004) is acknowledged.  ... 
doi:10.1007/978-3-642-19896-0_1 fatcat:7fscuhrszvdhvepauxrfs4w65a
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