Search results for "Semantic ambiguity"

showing 2 items of 2 documents

Building Semantic Trees from XML Documents

2016

International audience; The distributed nature of the Web, as a decentralized system exchanging information between heterogeneous sources, has underlined the need to manage interoperability, i.e., the ability to automatically interpret information in Web documents exchanged between different sources, necessary for efficient information management and search applications. In this context, XML was introduced as a data representation standard that simplifies the tasks of interoperation and integration among heterogeneous data sources, allowing to represent data in (semi-) structured documents consisting of hierarchically nested elements and atomic attributes. However, while XML was shown most …

Document Structure DescriptionComputer Networks and CommunicationsComputer sciencecomputer.internet_protocolSemantic analysis (machine learning)Efficient XML InterchangeInteroperabilityXML SignatureWord sense disambiguation02 engineering and technologycomputer.software_genreSemantic networkSemantic ambiguityXML Schema Editor020204 information systemsNode (computer science)0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]XML schemaContext representationcomputer.programming_languageXML treeInformation retrievalKnowledge basesSemi-structured dataXML validationcomputer.file_formatSemantic interoperabilityXMLHuman-Computer InteractionXML databaseSemantic similaritySemantic-aware processing020201 artificial intelligence & image processingWeb servicecomputerSoftwareXML
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I saw this somewhere else: the Spanish Ambiguous Words (SAW) database

2017

The present paper describes the Spanish Ambiguous Words (SAW) database, which comprises 210 words (133 polysemous and 77 homographs). Three-hundred and fifteen Spanish university students took part in the study on which SAW is based. First, subjective word meanings and senses were collected by means of a meaning retrieval task. Two judges then assigned participants’ responses to different categories of meaning according to lexicographical and statistical criteria. Results showed that, while there was a relatively high relationship between the number of senses included in the dictionary and those provided by participants (r = .62), regression analyses on lexical decision and naming times rev…

Linguistics and LanguageSocial SciencesMeaning (non-linguistic)Spanishcomputer.software_genreHomographs050105 experimental psychologyLanguage and LinguisticsSemantic ambiguityTask (project management)03 medical and health sciencesWord learning0302 clinical medicineLexical decision task:Psicologia [Ciências Sociais]0501 psychology and cognitive sciencesDatabase4. Education05 social sciencesPolysemous words16. Peace & justiceLinguisticsPredictive powerCiências Sociais::PsicologiaNormativePsychologycomputer030217 neurology & neurosurgeryWord (group theory)
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