Search results for " Extraction"

showing 10 items of 1344 documents

Does relevance matter to data mining research?

2008

Data mining (DM) and knowledge discovery are intelligent tools that help to accumulate and process data and make use of it. We review several existing frameworks for DM research that originate from different paradigms. These DM frameworks mainly address various DM algorithms for the different steps of the DM process. Recent research has shown that many real-world problems require integration of several DM algorithms from different paradigms in order to produce a better solution elevating the importance of practice-oriented aspects also in DM research. In this chapter we strongly emphasize that DM research should also take into account the relevance of research, not only the rigor of it. Und…

Knowledge extractionAssociation rule learningComputer scienceProcess (engineering)Granular computingInformation systemSoftware miningRelevance (information retrieval)Data miningcomputer.software_genreData sciencecomputerSketch
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On the use of information systems research methods in data mining

2006

Information systems are powerful instruments for organizational problem solving through formal information processing (Lyytinen, 1987). Data mining (DM) and knowledge discovery are intelligent tools that help to accumulate and process data and make use of it (Fayyad, 1996). Data mining bridges many technical areas, including databases, statistics, machine learning, and human-computer interaction. The set of data mining processes used to extract and verify patterns in data is the core of the knowledge discovery process. Numerous data mining techniques have recently been developed to extract knowledge from large databases. The area of data mining is historically more related to AI (Artificial…

Knowledge extractionComputer scienceProcess (engineering)Pattern recognition (psychology)Information systemProbabilistic logicTechnical reportInformation processingData miningcomputer.software_genrecomputerField (computer science)
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Natural Language-Based Knowledge Extraction in Healthcare Domain

2019

There is a growing amount of data in the databases of hospitals. These data could be exploited to alleviate the decision-making process of hospital managers, physicians and researchers. However, these types of end-users often lack the expertise necessary for extracting those data from the database. Several approaches exist in the field of how to allow non-programmers writing queries in a convenient manner, but none of them has yet reached fully satisfactory results. This paper sketches a solution to this problem by introducing means for writing queries in a keywords-containing natural language thus alleviating the query writing process for the end-user. Introducing this approach in the know…

Knowledge extractionComputer sciencebusiness.industryProcess (engineering)Health careWriting processQuery languagebusinessData scienceField (computer science)Natural languageDomain (software engineering)Proceedings of the 2019 3rd International Conference on Information System and Data Mining
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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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Knowledge Discovery from the Programme for International Student Assessment

2017

The Programme for International Student Assessment (PISA) is a worldwide study that assesses the proficiencies of 15-year-old students in reading, mathematics, and science every three years. Despite the high quality and open availability of the PISA data sets, which call for big data learning analytics, academic research using this rich and carefully collected data is surprisingly sparse. Our research contributes to reducing this deficit by discovering novel knowledge from the PISA through the development and use of appropriate methods. Since Finland has been the country of most international interest in the PISA assessment, a relevant review of the Finnish educational system is provided. T…

Knowledge managementmedia_common.quotation_subjectknowledge discoveryBig dataLearning analytics02 engineering and technologyKnowledge extractionbig data020204 information systemsReading (process)Political science0202 electrical engineering electronic engineering information engineeringMathematics educationQuality (business)Cluster analysismedia_commonStatistical hypothesis testinglearning analyticsbusiness.industry05 social sciencesPISA050301 educationTest (assessment)businesshierarchical clustering0503 education
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Feature Ranking of Large, Robust, and Weighted Clustering Result

2017

A clustering result needs to be interpreted and evaluated for knowledge discovery. When clustered data represents a sample from a population with known sample-to-population alignment weights, both the clustering and the evaluation techniques need to take this into account. The purpose of this article is to advance the automatic knowledge discovery from a robust clustering result on the population level. For this purpose, we derive a novel ranking method by generalizing the computation of the Kruskal-Wallis H test statistic from sample to population level with two different approaches. Application of these enlargements to both the input variables used in clustering and to metadata provides a…

Kruskal-Wallis testComputer scienceCorrelation clusteringPopulation02 engineering and technologycomputer.software_genreMachine learning01 natural sciencesRanking (information retrieval)010104 statistics & probabilityKnowledge extractionCURE data clustering algorithmpopulation analysisRanking SVM0202 electrical engineering electronic engineering information engineeringTest statistic0101 mathematicseducational knowledge discoveryeducationCluster analysiseducation.field_of_studybusiness.industryRanking020201 artificial intelligence & image processingData miningArtificial intelligencerobust clusteringbusinesscomputer
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Embedded controlled language to facilitate information extraction from eGov policies

2015

The goal of this paper is to propose a system that can extract formal semantic knowledge representation from natural language eGov policies. We present an architecture that allows for extracting Controlled Natural Language (CNL) statements from heterogeneous natural language texts with the ability to support multilinguality. The approach is based on the concept of embedded CNLs.

Language identificationNatural language user interfacebusiness.industryComputer scienceNatural language programmingcomputer.software_genrelanguage.human_languageInformation extractionUniversal Networking LanguageControlled natural languageQuestion answeringlanguageArtificial intelligencebusinesscomputerNatural language processingNatural languageProceedings of the 17th International Conference on Information Integration and Web-based Applications & Services
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tert-Butyl-calix[4]arenes Substituted at the Narrow Rim with Cobalt Bis(dicarbollide)(1–) and CMPO Groups – New and Efficient Extractants for Lanthan…

2007

Calix[4]arene derivatives bearing two residues A(–) derived from cobalt bis(dicarbollide)(1–) (1) and two CMPO groups B at their narrow rim were synthesized from tBu-calix[4]arene in four steps. The first step involved the preparation of tBu-calix[4]arene diether derivatives with appropriate precursors for amino groups (mostly nitriles 3). These were O-alkylated through ring-opening reactions with the zwitterionic dioxane derivative [(8-O(CH2CH2)2O-1,2-C2B9H10)-(1′,2′-C2B9H11)-3,3′-Co]0 (10) to produce ionic nitrile derivatives 4. Reduction of the nitrile groups with BH3·SMe2 (or deprotection in the case of the corresponding phthalimido or Boc derivatives 8) led to a series of diamines 5a–f…

LanthanideNitrileChemistryOrganic ChemistryIonic bondingNuclear magnetic resonance spectroscopyMedicinal chemistryAcylationchemistry.chemical_compoundLiquid–liquid extractionCalixareneOrganic chemistryPhysical and Theoretical ChemistryConformational isomerismEuropean Journal of Organic Chemistry
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Risk of laryngeal edema and facial swellings after tooth extraction in patients with hereditary angioedema with and without prophylaxis with C1 inhib…

2010

Objective Tooth extractions may trigger clinical symptoms of hereditary angioedema due to C1 inhibitor deficiency (HAE-C1-INH). The aim of this study was to determine how many tooth extractions were followed by symptoms of HAE-C1-INH in patients with and without preoperative short-term prophylaxis with C1 inhibitor concentrate. Study design Tooth extractions and clinical symptoms of HAE-C1-INH were determined from clinical record files of 171 patients with HAE-C1-INH. Results Facial swelling or potentially life-threatening laryngeal edema, or both, occurred in 124/577 tooth extractions (21.5%) without prophylaxis. Similar symptoms occurred in a fewer proportion of patients undergoing extrac…

LarynxAdultMalemedicine.medical_specialtyTime FactorsPremedicationComplement C1 Inactivator ProteinsLaryngeal EdemaChemopreventionC1-inhibitorRisk FactorsEdemamedicineEdemaHumansRisk factorGeneral DentistryRetrospective StudiesbiologyDose-Response Relationship Drugbusiness.industryAngioedemas HereditaryRetrospective cohort studyLaryngeal Edemamedicine.diseaseSurgerymedicine.anatomical_structureTreatment OutcomeOtorhinolaryngologyFaceHereditary angioedemaInjections IntravenousTooth Extractionbiology.proteinSurgeryPremedicationFemaleOral Surgerymedicine.symptombusinessComplement C1 Inhibitor ProteinFollow-Up StudiesOral surgery, oral medicine, oral pathology, oral radiology, and endodontics
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