0000000000263891

AUTHOR

Marco Viviani

showing 4 related works from this author

Towards semantic-based RSS merging

2009

Merging information can be of key importance in several XML-based applications. For instance, merging the RSS news from different sources and providers can be beneficial for end-users (journalists, economists, etc.) in various scenarios. In this work, we address this issue and mainly explore the relatedness relationships between RSS entities/ elements. To validate our approach, we also provide a set of experimental tests showing satisfactory results. © 2009 Springer-Verlag Berlin Heidelberg

Information retrievalComputer sciencecomputer.internet_protocolRSSINF/01 - INFORMATICAComputerApplications_COMPUTERSINOTHERSYSTEMScomputer.file_formatSet (abstract data type)Semantic similarityArtificial IntelligenceKey (cryptography)Document Object ModelcomputerXML
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Semantic-based Merging of RSS Items

2009

Merging XML documents can be of key importance in several applications. For instance, merging the RSS news from same or different sources and providers can be beneficial for end-users in various scenarios. In this paper, we address this issue and explore the relatedness measure between RSS elements. We show here how to define and compute exclusive relations between any two elements and provide several predefined merging operators that can be extended and adapted to human needs. We also provide a set of experiments conducted to validate our approach. © Springer Science+Business Media, LLC 2009.

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer Networks and CommunicationsComputer sciencecomputer.internet_protocolRSS[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologycomputer.software_genreClusteringMergingSet (abstract data type)[SCCO.COMP] Cognitive science/Computer science020204 information systems0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Cluster analysisComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]Measure (data warehouse)[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Document relatedne[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]computer.file_formatRSSMerging operator[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Hardware and Architecture[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Key (cryptography)020201 artificial intelligence & image processingData mining[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computerSoftwareXML
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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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A Community-based Approach for Service-based Application Composition in an Ecosystem

2010

The design of composite applications by combining existing services with known semantics is an ongoing topic in current research. Several studies are aimed at providing service description models and standards, service discovery and matching etc. However, service composition in distributed dynamic environments such as P2P ecosystems has received little attention from research communities. In this paper we present a design framework for composing services, taking in particular into account different ways of building peercommunities based on network or services characteristics.

Service (business)Matching (statistics)Computer sciencecomputer.internet_protocolbusiness.industryEnvironmental resource managementService discoveryOverlay networkService-oriented architectureSemanticsData scienceEcosystemService-based Application CompositionbusinesscomputerComposition (language)
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