Search results for "Domain knowledge"

showing 10 items of 27 documents

Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions

2022

The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…

FOS: Computer and information sciencesComputer Science - Machine LearningEarth observationAdvanced microwave scanning radiometer-2 (AMSR-2)moderate resolution imaging spectroradiometer (MODIS)Computer scienceleaf area index (LAI)0211 other engineering and technologiesExtrapolationMachine Learning (stat.ML)02 engineering and technologycomputer.software_genreMachine Learning (cs.LG)Data-drivenConvolutionsymbols.namesakeadvanced scatterometer (ASCAT)Statistics - Machine Learningordinary differential equation (ODE)Electrical and Electronic EngineeringGaussian processsoil moisture and ocean salinity (SMOS)021101 geological & geomatics engineeringInterpretabilityForcing (recursion theory)machine learning (ML)soil moisture (SM)time series analysisgaussian process (GP)symbolsGeneral Earth and Planetary SciencesDomain knowledgeData mininggap fillingphysicscomputerfraction of absorbed photosynthetically active radiation (faPAR)IEEE Transactions on Geoscience and Remote Sensing
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Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift

2010

Fuel feeding and inhomogeneity of fuel typically cause fluctuations in the circulating fluidized bed (CFB) process. If control systems fail to compensate the fluctuations, the whole plant will suffer from dynamics that is reinforced by the closed-loop controls. This phenomenon causes reducing efficiency and the lifetime of process components. In this paper we address the problem of online mass flow prediction, which is a part of control. Particularly, we consider the problem of learning an accurate predictor with explicit detection of abrupt concept drift and noise handling mechanisms. We emphasize the importance of having domain knowledge concerning the considered case and constructing the…

Ground truthConcept driftComputer scienceMass flowGeography Planning and DevelopmentBoiler (power generation)Control theoryControl systemGeneral Earth and Planetary SciencesDomain knowledgeFluidized bed combustionChange detectionSimulationWater Science and Technology
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Transferable and Negotiated Knowledge

2002

• Summary: This article explores the knowledge of community-based social workers in the context of an action research project aimed at exploring the practitioners’ own descriptions of their knowledge and expertise on the theme of spatial marginalization. • Findings: The knowledge of social workers seemed to be based on service users’ experiences and case examples, on value and moral constructions, and it was created from experience, by doing and in action. It was local and contextual, in some sense silent but shared through a discussion process. It was not based on empirically based scientific research understood in the traditional sense; rather, social workers resorted to practical knowle…

Health (social science)Knowledge managementSocial workbusiness.industry05 social sciencesTransferabilityKnowledge value chainContext (language use)Social relation0506 political science0502 economics and business050602 political science & public administrationPersonal knowledge managementDomain knowledgeSociologyAction researchbusiness050203 business & managementSocial Sciences (miscellaneous)Journal of Social Work
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Enriching Didactic Similarity Measures of Concept Maps by a Deep Learning Based Approach

2021

Concept maps are significant tools able to support several tasks in the educational area such as curriculum design, knowledge organization and modeling, students' assessment and many others. They are also successfully used in learning activities in which students have to represent domain knowledge according to teacher's assignment. In this context, the development of Learning Analytics approaches would benefit of methods that automatically compare concept maps. Detecting concept maps similarities is relevant to identify how the same concepts are used in different knowledge representations. Algorithms for comparing graphs have been extensively studied in the literature, but they do not appea…

Information retrievalLearning AnalyticKnowledge representation and reasoningComputer scienceConcept mapKnowledge organizationLearning analyticsContext (language use)SemanticsLearning AnalyticsConcept MapConcept MapsDeep LearningInfersentSimilarity (psychology)Semantic Similarity MeasuresDomain knowledgeNatural Language Processing
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Knowledge management challenges in knowledge discovery systems

2006

Current knowledge discovery systems are armed with many data mining techniques that can be potentially applied to a new problem. However, a system faces a challenge of selecting the most appropriate technique(s) for a problem at hand, since in the real domain area it is infeasible to perform a comparison of all applicable techniques. The main goal of this paper is to consider the limitations of data-driven approaches and propose a knowledge-driven approach to enhance the use of multiple data-mining strategies in a knowledge discovery system. We introduce the concept of (meta-) knowledge management, which is aimed to organize a systematic process of (meta-) knowledge capture and refinement o…

Knowledge managementCommonsense knowledgebusiness.industryComputer scienceData managementKnowledge engineeringOpen Knowledge Base ConnectivityMathematical knowledge managementData scienceKnowledge-based systemsKnowledge extractionKnowledge basePersonal knowledge managementSoftware miningDomain knowledgebusiness
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Comparing the applicability of two learning theories for knowledge transfer in information system implementation training

2004

This study reviews two traditional learning theories from the viewpoint of knowledge transfer in information system implementation training. The main goal of this study is to determine which is more applicable from the view of knowledge transfer in this context. In this study, behaviourist learning theory is found suitable for the transfer of data and information. Being more learner-centered, constructivist learning theory suits better for information system implementation training, as it enables combining system specific knowledge with knowledge of the existing organisational processes. This creates new organisation-specific knowledge necessary for the effective use of the information syst…

Knowledge managementbusiness.industryComputer scienceKnowledge engineeringOpen Knowledge Base ConnectivityKnowledge value chainMathematical knowledge managementProcedural knowledgeConstructivist teaching methodsBody of knowledgeKnowledge-based systemsKnowledge baseKnowledge extractionKnowledge integrationOrganizational learningInformation systemLearning theoryPersonal knowledge managementDomain knowledgebusinessKnowledge transferIEEE International Conference on Advanced Learning Technologies, 2004. Proceedings.
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Where to acquire knowledge: Adapting knowledge management to financial institutions

2016

Abstract This research seeks to determine which sources of knowledge have the greatest effect on financial entities' knowledge acquisition and management. A review of the literature on knowledge management examines four key knowledge sources: Human resources, organizational management, technology adoption, and the business environment. The study performs pairwise comparisons of variables through the analytic hierarchy process (AHP), using a scale that captures the importance of each criterion, thereby simplifying the decision process. Results show that human resources and new technology adoption are the most effective sources of knowledge acquisition and management. Specifically, one of the…

MarketingFinanceKnowledge managementComputer sciencebusiness.industryKnowledge economy05 social sciencesKnowledge engineeringKnowledge value chain02 engineering and technologyProcedural knowledgeBody of knowledge020204 information systems0502 economics and businessOrganizational learning0202 electrical engineering electronic engineering information engineeringPersonal knowledge managementDomain knowledgebusiness050203 business & managementJournal of Business Research
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Knowledge Acquisition from Multiple Experts Based on Semantics of Concepts

1999

This paper presents one approach to acquire knowledge from multiple experts. The experts are grouped into a multilevel hierarchical structure, according to the type of knowledge acquired. The first level consists of experts who have knowledge about the basic objects and their relationships. The second level of experts includes those who have knowledge about the relationships of the experts at the first level and each higher level accordingly. We show how to derive the most supported opinion among the experts at each level. This is used to order the experts into categories of their competence defined as the support they get from their colleagues.

Multiple expertsKnowledge representation and reasoningComputer sciencebusiness.industryConceptual graphDomain knowledgeArtificial intelligencebusinessCompetence (human resources)Data scienceKnowledge acquisition
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A Dynamic Reasoning Architecture for Computer Network Management

2005

This paper focuses on improving network management and monitoring by the adoption of Artificial Intelli- gence techniques. In order to allow automated reasoning on networking concepts, we defined an accurate ontologi- cal model capable of describing as better as possible the networking domain. The thorough representation of the do- main knowledge is used by a Logical Reasoner, which is an expert system capable of performing high-level manage- ment tasks.

Reasoning systemArtificial architectureOpportunistic reasoningKnowledge representation and reasoningbusiness.industryComputer scienceMulti-agent systemRule-based systemMarketing and artificial intelligenceLegal expert systemSemantic reasonerModel-based reasoningcomputer.software_genreExpert systemArtificial intelligence situated approachProcedural reasoning systemOntologyDomain knowledgecomputer network managementAutomated reasoningArtificial intelligencebusinessSoftware engineeringcomputer
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A Knowledge Management System using Bayesian Network

2009

In today's world, decision support and knowledge management processes are strategic and interdependent activities in many organizations. The companies' interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. This paper proposes a Knowledge Management System based on Bayesian networks. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and a Decision Support system to share documents and to plan how to best use firms' knowledge.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniDecision support systemKnowledge managementbusiness.industryComputer scienceData managementKnowledge engineeringKnowledge value chainIntelligent decision support systemDocument management systemProcedural knowledgecomputer.software_genreClinical decision support systemKnowledge-based systemsKnowledge extractionKnowledge baseInformation and Communications TechnologyOrganizational learningPersonal knowledge managementOntologyDomain knowledgeKnowledge Management Bayesian Network Artificial Intelligencebusinesscomputer
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