Search results for "Heterogeneous information"

showing 3 items of 3 documents

SESAMO: An integrated framework for gathering, managing and sharing environmental data

2016

ICT systems are widely adopted for environmental management, but existing solutions address limited tasks and compose a plethora of heterogeneous tools, which impose a great additional effort on the operators. This work presents SESAMO, a novel framework to provide the operators with a unique tool for gathering, managing and merging environmental and territorial data. SESAMO uses WSNs for providing pervasive monitoring of environmental phenomena and exploits a multi-tier infrastructure in order to integrate data coming from heterogeneous information sources.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge managementEnvironmental managementExploitSESAMOComputer sciencebusiness.industryPervasive sensing020206 networking & telecommunications02 engineering and technologyData scienceEnvironmental dataHuman-Computer InteractionComputer Networks and CommunicationWork (electrical)Information and Communications TechnologyOrder (exchange)Computer systems and technologie0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingHeterogeneous informationbusinessSoftware
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From Signal Processing to Machine Learning

2018

This chapter reviews the main landmarks of signal processing in the 20th century from the perspective of algorithmic developments. It focuses on cross‐fertilization with the field of statistical (machine) learning in the last decades. In the 21st century, model and data assumptions as well as algorithmic constraints are no longer valid, and the field of machine‐learning signal processing has erupted, with many successful stories to tell. The chapter also focuses on digital signal processing (DSP), which deals with the analysis of digitized and discrete sampled signals. Machine learning is a branch of computer science and artificial intelligence that enables computers to learn from data. Mac…

Signal processingbusiness.industryComputer sciencePerspective (graphical)Machine learningcomputer.software_genreField (computer science)Improved performanceOnline adaptationHeterogeneous informationArtificial intelligencebusinesscomputerDigital signal processing
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Customizing Semantic Profiling for Digital Advertising

2014

International audience; Personalization is the new magic buzzword of application development. To make the complexity of today's application functionalities and information spaces "digestible", customization has become the new go-to technique. But while those technologies aim to ease the consumption of media for their users, they suffer from the same problematic: in the age of Big Data, applications have to cope with a conundrum of heterogeneous information sources that have to be perceived, processed and interpreted. Researchers tend to aim for a maximum degree of integration to create the perfect, all-embracing personalization. The results are wide-range, but overly complex systems that su…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO ] Computer Science [cs]Computer scienceBig dataComplex systemsemantic technologies02 engineering and technology[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]Personalization[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]World Wide Web020204 information systems0202 electrical engineering electronic engineering information engineeringProfiling (information science)Heterogeneous information[ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO]Computer Science [cs]user profiles[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]OWLuser profilingbusiness.industryScalabilitySemantic technology020201 artificial intelligence & image processingbusinessDigital advertisingcustomization
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