Search results for "Language processing"

showing 10 items of 421 documents

More Than (Single) Text Comprehension? – On University Students’ Understanding of Multiple Documents

2020

The digital revolution has made a multitude of text documents from highly diverse perspectives on almost any topic easily available. Accordingly, the ability to integrate and evaluate information from different sources, known as multiple document comprehension, has become increasingly important. Because multiple document comprehension requires the integration of content and source information across texts, it is assumed to exceed the demands of single text comprehension due to the inclusion of two additional mental representations: the integrated situation model and the intertext model. To date, there is little empirical evidence on commonalities and differences between single text and mult…

Structure (mathematical logic)business.industryassessmentlcsh:BF1-990Regression analysismultiple document comprehensioncomputer.software_genrereading comprehensionComprehensionsingle text comprehensionlcsh:PsychologyEmpirical researchReading comprehensionMental representationPsychologyArtificial intelligenceuniversity studentsbusinessPsychologyEmpirical evidenceConstruct (philosophy)computerNatural language processingGeneral PsychologyOriginal ResearchFrontiers in Psychology
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Analyzing the Effects of Lexical Cognates on Translation Properties: A Multivariate Product and Process Based Approach

2021

The translation of cognates has received renewed interest in Translation Process Research (Oster (2017) Empir Model Transl Interpret 7:23; Hansen-Schirra et al. (2017) Predicting cognate translation. In: Hansen-Schirra S, Czulo O, Hofmann S (eds) Empirical modelling of translation and interpreting. Language Science Press, Berlin, pp 3–22) but tends to be relatively time-consuming due to the manual identification of cognates and their translations. On the basis of work by Heilmann (Profiling effects of syntactic complexity in translation: a multi-method approach. PhD thesis, 2021) and the structure of the TPR-DB, we devised a relatively simple way to determine the cognate status of ST words …

Structure (mathematical logic)business.industrymedia_common.quotation_subjectLiteral translationAmbiguitycomputer.software_genreReading (process)Similarity (psychology)Literal (computer programming)CognateArtificial intelligenceAffect (linguistics)businessPsychologycomputerNatural language processingmedia_common
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The influence of task-irrelevant music on language processing: syntactic and semantic structures.

2011

Recent research has suggested that music and language processing share neural resources, leading to new hypotheses about interference in the simultaneous processing of these two structures. The present study investigated the effect of a musical chord's tonal function on syntactic processing (Experiment 1) and semantic processing (Experiment 2) using a cross-modal paradigm and controlling for acoustic differences. Participants read sentences and performed a lexical decision task on the last word, which was, syntactically or semantically, expected or unexpected. The simultaneously presented (task-irrelevant) musical sequences ended on either an expected tonic or a less-expected subdominant ch…

SubdominantDeep linguistic processingComputer sciencelcsh:BF1-990structural integrationMusicalcomputer.software_genremusical expectancy050105 experimental psychology03 medical and health sciences0302 clinical medicineLexical decision taskSemantic memoryPsychology0501 psychology and cognitive sciencesGeneral PsychologyOriginal Researchbusiness.industryMusical syntax05 social sciencessemantic expectancySyntaxsyntactic expectancylcsh:PsychologyChord (music)Artificial intelligencecross-modal interactionsbusinesscomputer030217 neurology & neurosurgeryNatural language processingFrontiers in psychology
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Visualization in comparative music research

2007

Computational analysis of large musical corpora provides an approach that overcomes some of the limitations of manual analysis related to small sample sizes and subjectivity. The present paper aims to provide an overview of the computational approach to music research. It discusses the issues of music representation, musical feature extraction, digital music collections, and data mining techniques. Moreover, it provides examples of visualization of large musical collections.

SubjectivityInformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.HCI)Computer sciencebusiness.industryFeature extractionRepresentation (systemics)Small sampleMusicalcomputer.software_genreVisualizationComputational musicologyArtificial intelligencebusinesscomputerNatural language processingDigital audio
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Symbolic Reductionist Model for Program Comprehension

2007

This article presents the main features of a novel construction, symbolic analysis, for automatic source code processing. The method is superior to the known methods, because it uses a semiotic, interpretative approach. Its most important processes and characteristics are considered here. We describe symbolic information retrieval and the process of analysis in which it can be used in order to obtain pragmatic information. This, in turn, is useful in understanding a current Java program version when developing a new version.

Symbolic programmingObject-oriented programmingSource codeComputer scienceProgramming languagebusiness.industrymedia_common.quotation_subjectProgram comprehensioncomputer.software_genreSymbolic data analysisReal time JavaSymbolic trajectory evaluationArtificial intelligencebusinessJava annotationcomputerNatural language processingmedia_common2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)
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A Hidden Markov Model for Automatic Generation of ER Diagrams from OWL Ontology

2014

Connecting ontological representations and data models is a crucial need in enterprise knowledge management, above all in the case of federated enterprises where corporate ontologies are used to share information coming from different databases. OWL to ERD transformations are a challenging research field in this scenario, due to the loss of expressiveness arising when OWL axioms have to be represented using ERD notation. In this paper we propose an innovative technique for estimating the most likely composition of ERD constructs that correspond to a given sequence of OWL axioms. We model such a process using a Hidden Markov Model (HMM) where the OWL inputs are the observable states, while E…

Syntax (programming languages)Computer sciencebusiness.industrycomputer.internet_protocolWeb Ontology Languagecomputer.software_genreNotationOWL-SData modelingSet (abstract data type)Entity–relationship modelArtificial intelligenceHidden Markov modelbusinesscomputerNatural language processingcomputer.programming_language2014 IEEE International Conference on Semantic Computing
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Graphical Template Language for Transformation Synthesis

2010

Higher-Order Transformations (HOT) have become an important support for the development of model transformations in various transformation languages. Most frequently HOTs are used to synthesize transformations from different kinds of models, for example, mapping models. This means that model driven development (MDD) is being successfully applied to transformations themselves too. The standard HOT solution is to create the transformation as a model using the abstract syntax. However, for graphical transformation languages a significantly more efficient solution would be to create the transformation using its graphical (concrete) syntax. An analogy could be the textual template languages such…

Syntax (programming languages)business.industryProgramming languageComputer scienceModel transformationAnalogycomputer.software_genreTransformation languageDevelopment (topology)Concrete syntaxTransformation (function)Abstract syntaxArtificial intelligencebusinesscomputerNatural language processingcomputer.programming_language
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Comments on “Overviews of Models Defined with Charts of Concepts” by X. Castellani

2000

This paper has introduced a simplified model for the representation of system development methods. The model forms charts of concepts. Different from other metamodels that are made to explain methods in details, the charts of concepts are to help understanding of the concepts of methods using graphic presentation.

System developmentPresentationbusiness.industryComputer sciencemedia_common.quotation_subjectRepresentation (systemics)Artificial intelligencebusinesscomputer.software_genrecomputerNatural language processingmedia_common
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Correction: Mechanical properties of provisional dental materials: A systematic review and meta-analysis.

2018

Provisional restorations represent an important phase during the rehabilitation process, knowledge of the mechanical properties of the available materials allows us to predict their clinical performance. At present, there is no systematic review, which supports the clinicians’ criteria, in the selection of a specific material over another for a particular clinical situation. The purpose of this systematic review and meta-analysis was to assess and compare the mechanical properties of dimethacrylates and monomethacrylates used in fabricating direct provisional restorations, in terms of flexural strength, fracture toughness and hardness. This review followed the PRISMA guidelines. The searche…

TeethComputer sciencePolymerslcsh:MedicineChemical Composition02 engineering and technologycomputer.software_genre01 natural sciencesPolymerizationMathematical and Statistical TechniquesMedicine and Health Scienceslcsh:Science010302 applied physicsMultidisciplinaryChemical ReactionsResearch Assessment021001 nanoscience & nanotechnologyChemistryMacromoleculesMeta-analysisPhysical SciencesAnatomy0210 nano-technologyPlasticsNatural language processingStatistics (Mathematics)Research ArticleSystematic ReviewsMaterials by StructureMaterials ScienceMaterial PropertiesResearch and Analysis MethodsText mining0103 physical sciencesMechanical PropertiesStatistical MethodsMaterials by Attributebusiness.industrylcsh:RBiology and Life SciencesPolymer ChemistryJawlcsh:QArtificial intelligencebusinesscomputerDigestive SystemHeadMathematicsMeta-AnalysisPLoS ONE
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Analysis and Comparison of Deep Learning Networks for Supporting Sentiment Mining in Text Corpora

2020

In this paper, we tackle the problem of the irony and sarcasm detection for the Italian language to contribute to the enrichment of the sentiment analysis field. We analyze and compare five deep-learning systems. Results show the high suitability of such systems to face the problem by achieving 93% of F1-Score in the best case. Furthermore, we briefly analyze the model architectures in order to choose the best compromise between performances and complexity.

Text corpusComputer sciencemedia_common.quotation_subjectCompromiseFace (sociological concept)02 engineering and technologycomputer.software_genreField (computer science)020204 information systems0202 electrical engineering electronic engineering information engineeringnatural language processingmedia_commonSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - InformaticaSarcasmbusiness.industryDeep learningSentiment analysisdeep learningirony detectionIrony020201 artificial intelligence & image processingArtificial intelligencebusinesscomputersarcasm detectionNatural language processingProceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services
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