Search results for "Vector space model"

showing 4 items of 4 documents

Relating RSS News/Items

2009

Merging related RSS news (coming from one or different sources) is beneficial for end-users with different backgrounds (journalists, economists, etc.), particularly those accessing similar information. In this paper, we provide a practical approach to both: measure the relatedness, and identify relationships between RSS elements. Our approach is based on the concepts of semantic neighborhood and vector space model, and considers the content and structure of RSS news items. © 2009 Springer Berlin Heidelberg.

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer scienceRSS[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologySimilarityTheoretical Computer ScienceWorld Wide Web[SCCO.COMP] Cognitive science/Computer science020204 information systemsSimilarity (psychology)0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Neighbourhood (mathematics)[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]Structure (mathematical logic)[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Measure (data warehouse)[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Information retrievalRelationship[INFO.INFO-WB]Computer Science [cs]/WebComputer Science (all)[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]computer.file_format[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]RSS Relatedne[ SCCO.COMP ] Cognitive science/Computer scienceVector space model020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]InformationSystems_MISCELLANEOUSNeighbourhoodcomputer
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Extensible User-Based XML Grammar Matching

2009

International audience; XML grammar matching has found considerable interest recently due to the growing number of heterogeneous XML documents on the web and the increasing need to integrate, and consequently search and retrieve XML data originated from different data sources. In this paper, we provide an approach for automatic XML grammar matching and comparison aiming to minimize the amount of user effort required to perform the match task. We propose an open framework based on the concept of tree edit distance, integrating different matching criterions so as to capture XML grammar element semantic and syntactic similarities, cardinality and alternativeness constraints, as well as data-ty…

Document Structure Description[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]XML Encryption[INFO.INFO-WB] Computer Science [cs]/WebComputer sciencecomputer.internet_protocolEfficient XML Interchange[ INFO.INFO-WB ] Computer Science [cs]/WebXML Signature[SCCO.COMP]Cognitive science/Computer science02 engineering and technologycomputer.software_genreSchema matchingSimple API for XML[SCCO.COMP] Cognitive science/Computer scienceXML Schema Editor020204 information systemsStreaming XML0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]RELAX NGXML schemaBinary XMLSGML[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]computer.programming_language[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Information retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]XML validationcomputer.file_formatXML framework[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]XML databaseXML Schema (W3C)[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Vector space model020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computerXMLXML Catalog
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Semantic Computing of Moods Based on Tags in Social Media of Music

2014

Social tags inherent in online music services such as Last.fm provide a rich source of information on musical moods. The abundance of social tags makes this data highly beneficial for developing techniques to manage and retrieve mood information, and enables study of the relationships between music content and mood representations with data substantially larger than that available for conventional emotion research. However, no systematic assessment has been done on the accuracy of social tags and derived semantic models at capturing mood information in music. We propose a novel technique called Affective Circumplex Transformation (ACT) for representing the moods of music tracks in an interp…

FOS: Computer and information sciencesVocabularyComputer scienceMusic information retrievalmedia_common.quotation_subjectSemantic analysis (machine learning)Moodscomputer.software_genreAffect (psychology)SemanticsComputer Science - Information RetrievalSemantic computingMusic information retrievalAffective computingmedia_commonSocial and Information Networks (cs.SI)ta113Probabilistic latent semantic analysisSocial tagsbusiness.industryComputer Science - Social and Information NetworksMultimedia (cs.MM)Semantic analysisComputer Science ApplicationsMoodComputational Theory and MathematicsWeb miningta6131Vector space modelArtificial intelligenceGenresbusinesscomputerComputer Science - MultimediaInformation Retrieval (cs.IR)MusicNatural language processingPrediction.Information SystemsIEEE Transactions on Knowledge and Data Engineering
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Part-of-speech labeling for Reuters database

2015

Even if the Vector Space Model used for document representation in information retrieval systems integrates a small quantity of knowledge it continues to be used due to its computational cost, speed execution and simplicity. We try to improve this document representation by adding some syntactic information such as the parts of speech. In this paper, we have evaluated three different tagging algorithms in order to select the most suitable tagger for using it to tag the Reuters dataset. In this work, we have evaluated the taggers using only five different parts of speech: noun, verb, adverb, adjective and others. We considered these particular tags being the most representative for describin…

Information retrievalbusiness.industryComputer scienceInformationSystems_INFORMATIONSTORAGEANDRETRIEVALVerbAdverbSpace (commercial competition)Part of speechcomputer.software_genreSequence labelingNounVector space modelArtificial intelligencebusinesscomputerAdjectiveNatural language processing2015 19th International Conference on System Theory, Control and Computing (ICSTCC)
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