Search results for " Inference"

showing 10 items of 337 documents

Mindfulness, empatía y compasión: Evolución de la empatía a la compasión en el ámbito sanitario

2019

En el ámbito de la atención a la salud mental, la empatía es un aspecto especialmente importante, ya que supone la base sobre la que se sostiene elvínculo terapéutico y se articulan las diferentes actuaciones psicológicas, al facilitar un entendimiento de la vida y de las situaciones de los pacientes. En este sentido, las intervenciones basadas en mindfulness y compasión (IBMC) se han mostrado efectivas para aumentar la empatía en los profesionales sanitarios. Sin embargo, actualmente siguen existiendo algunas inconsistencias en el estudio de la empatía y su relación con mindfulness y compasión. En este artículo, se expone una visión global de estos constructos, subrayando la importancia de…

NurseryMedicinaSesgos en la InferenciaClinical and Health PsychologyGeneral MedicineCompasiónPsicología Clínica y de la SaludPsychotherapyPsicoterapiaCompassionMedicineEnfermeríaBiases in the InferenceEmpathyMindfulnessPhysical therapyEmpatíaFisioterapiaDeportesSportsRevista de Investigación y Educación en Ciencias de la Salud (RIECS)
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Semantics driven interaction using natural language in students tutoring

2007

The aim of this work is to introduce a semantic integration between an ontology and a chatbot in an Intelligent Tutoring Systems (ITS) to interact with students using natural language. The interaction process is driven by the use of a purposely defined ontology. In the ontology two types of conceptual relations are defined. Besides the usual relations, which are used to define the domain's structure, another type of relation is used to define the navigation schema inside the ontology according to the need of managing uncertainty. Uncertainty level is related to student knowledge level about the involved concepts. In this work we propose an ITS for the Java programming language called TutorJ…

Ontology Inference LayerComputer sciencecomputer.internet_protocolOntology (information science)Semanticscomputer.software_genreOWL-SIntelligent tutoring systemsLatent semantic analysisNatural language dialogueSemantic driven interactionSemantic navigationSemantic similaritySemantic computingSchema (psychology)Upper ontologySemantic integrationSemantic compressionSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionisemantic navigationLatent semantic analysisbusiness.industryOntology-based data integrationKnowledge levelIntelligent Tutoring SystemsOntologylatent semantic analysisArtificial intelligencesemantic driven interactionbusinesscomputernatural language dialogueNatural language processing
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A literature review of sensor ontologies for manufacturing applications

2013

The purpose of this paper is to review existing sensor and sensor network ontologies to understand whether they can be reused as a basis for a manufacturing perception sensor ontology, or if the existing ontologies hold lessons for the development of a new ontology. We develop an initial set of requirements that should apply to a manufacturing perception sensor ontology. These initial requirements are used in reviewing selected existing sensor ontologies. Additionally, we present our developed sensor ontology thus far that incorporates a refined list of requirements. This paper describes 1) extending and refining the requirements; 2) proposing hierarchical structures for verifying the purpo…

Ontology Inference LayerDatabaseComputer sciencebusiness.industrycomputer.internet_protocolOntology-based data integrationProcess ontologySuggested Upper Merged OntologyOntology (information science)computer.software_genreOWL-SUpper ontologySoftware engineeringbusinesscomputerOntology alignment2013 IEEE International Symposium on Robotic and Sensors Environments (ROSE)
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A Survey on Ontology Evaluation Methods

2015

International audience; Ontologies nowadays have become widely used for knowledge representation, and are considered as foundation for Semantic Web. However with their wide spread usage, a question of their evaluation increased even more. This paper addresses the issue of finding an efficient ontology evaluation method by presenting the existing ontology evaluation techniques, while discussing their advantages and drawbacks. The presented ontology evaluation techniques can be grouped into four categories: gold standard-based, corpus-based, task-based and criteria based approaches.

Ontology Inference Layer[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-TT ] Computer Science [cs]/Document and Text ProcessingComputer sciencecomputer.internet_protocolProcess ontology[ INFO.INFO-WB ] Computer Science [cs]/Web02 engineering and technologyOntology (information science)OWL-S[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]020204 information systems0202 electrical engineering electronic engineering information engineeringUpper ontology[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]EvaluationInformation retrievalOntologyOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebSuggested Upper Merged Ontology[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-TT]Computer Science [cs]/Document and Text Processing[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]020201 artificial intelligence & image processing[ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO]computerOntology alignmentSemantic web
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Ontology Views for Ontology Change Management

2014

International audience; In the literature, ontology change management systems (OCMS) are direct implementation of the concept of “change management” stated by reference (Klein, 2004). Ontology change management combines ontol- ogy evolution and versioning features to manage ontol- ogy changes and their impacts. Since 2007, many works have combined ontology evolution and versioning into ontology change management systems (OCMS). The evolution subject has been massively studied in these works. They especially addressed the consistence issue for the application of changes on the ontology. These proposals constituted a consequent background for ontology change management but they did not take i…

Ontology Inference Layer[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationComputer scienceProcess ontologyURI[ INFO.INFO-WB ] Computer Science [cs]/Web02 engineering and technologyOntology (information science)computer.software_genreRDFOpen Biomedical Ontologies[INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]ontology evolution0202 electrical engineering electronic engineering information engineeringUpper ontologyontologyOWL DLOWLInformation retrievalOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebSuggested Upper Merged Ontologymaterialized view020207 software engineering[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation[ INFO.INFO-FL ] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]database viewontology mapping020201 artificial intelligence & image processingData miningComputingMethodologies_GENERALontology change managementOntology alignmentcomputer
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Modeling Changes for SHOIN(D) Ontologies: An Exhaustive Structural Model

2013

Ontology development starts with a rigorous ontological analysis that provides a conceptualization of the domain to model agreed by the community. An ontology, specified in a formal language, approximates the intended models of this conceptualization. It needs then to be revised and refined until an ontological commitment is found. Also ulterior updates, responding to changes in the domain and/or the conceptualization, are expected to occur throughout the ontology life cycle. To handle a consistent application of changes, a couple of ontology evolution methodologies have been proposed. Maintaining the structural consistency is one of the ontology evolution criteria. It implies modeling chan…

Ontology Inference Layer[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-WB] Computer Science [cs]/WebComputer scienceProcess ontology030303 biophysicsData_MISCELLANEOUS[ INFO.INFO-WB ] Computer Science [cs]/Web02 engineering and technologyOntology (information science)computer.software_genre03 medical and health sciencesOntology chart[INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]SHOIN(D) Description LogicOntology components0202 electrical engineering electronic engineering information engineeringUpper ontologyOWL DL[INFO.INFO-FL] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]0303 health sciencesbusiness.industryOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebSuggested Upper Merged Ontology[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]Structural ConsistencyOntology EvolutionIEEE[ INFO.INFO-FL ] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]Ontology Model020201 artificial intelligence & image processing[ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO]Artificial intelligenceComputingMethodologies_GENERALChange ModellingbusinesscomputerNatural language processing
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Model Driven Specification of Ontology Translations

2008

The alignment of different ontologies requires the specification, representation and execution of translation rules. The rules need to integrate translations at the lexical, the syntactic and the semantic layer requiring semantic reasoning as well as low-level specification of ad-hoc conversions of data. Existing formalisms for representing translation rules cannot cover the representation needs of these three layers in one model. We propose a metamodel-based representation of ontology alignments that integrate semantic translations using description logics and lower level translation specifications into one model of representation for ontology alignments.

Ontology Inference Layerbusiness.industryProgramming languageComputer scienceOntology-based data integrationProcess ontologySuggested Upper Merged Ontology02 engineering and technologyOntology (information science)computer.software_genreDescription logic020204 information systems0202 electrical engineering electronic engineering information engineeringUpper ontology020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerOntology alignmentNatural language processingLecture Notes in Computer Science Conceptual Modeling - ER 2008
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Data Mining of Specific-Domain Ontology Components

2008

This paper describes an approach for eliciting ontology components by using knowledge maps. The knowledge contained in a particular domain, any kind of text digital archive, is portrayed by assembling and displaying its ontology components.

Open Biomedical OntologiesOntology Inference LayerInformation retrievalComputer scienceOntology-based data integrationOntology componentsProcess ontologySuggested Upper Merged OntologyUpper ontologyData miningOntology (information science)computer.software_genrecomputer
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Semi-automatic Derivation of Specific-Domain Ontologies for the Semantic Web

2006

This paper describes an approach for helping in the semi-automatic construction of specific-domain ontology components contained in a digital archive. This proposal for extracting knowledge from digital sources allows users to have a view of this knowledge and visualize specific-domain ontology components that with further processing can be shared with software agents by embedding it into digital archives themselves in the context of the Semantic Web. In particular, we deal with the issue of not constructing the ontology from scratch, our approach helps us to speed up the ontology creation process.

Open Biomedical OntologiesWorld Wide WebOntology Inference LayerInformation retrievalComputer sciencecomputer.internet_protocolProcess ontologyOntology-based data integrationSuggested Upper Merged OntologyUpper ontologyOntology (information science)computerOWL-S2006 Fifth Mexican International Conference on Artificial Intelligence
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A systematic approach to deriving incremental type checkers

2020

Static typing can guide programmers if feedback is immediate. Therefore, all major IDEs incrementalize type checking in some way. However, prior approaches to incremental type checking are often specialized and hard to transfer to new type systems. In this paper, we propose a systematic approach for deriving incremental type checkers from textbook-style type system specifications. Our approach is based on compiling inference rules to Datalog, a carefully limited logic programming language for which incremental solvers exist. The key contribution of this paper is to discover an encoding of the infinite typing relation as a finite Datalog relation in a way that yields efficient incremental up…

Operator overloadingRelation (database)Computer scienceProgramming languageInferencecomputer.software_genreDatalogSimple (abstract algebra)CompilerSafety Risk Reliability and QualityRule of inferencecomputerSoftwareLogic programmingcomputer.programming_languageProceedings of the ACM on Programming Languages
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