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Jean Paul Calbimonte Perez

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Publications associées (26)

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Semantic representation and processing of hypoglycemic events derived from wearable sensor data

Karl Aberer, Jean Paul Calbimonte Perez, Jean-Eudes Marie Ranvier

Diabetes Type 1 is a metabolic disease which results in a lack of insulin production, causing high glucose levels in the blood. It is crucial for diabetic patients to balance this glucose level, and they depend on external substances to do so. In order to ...

Ios Press2017

Toward Semantic Sensor Data Archives on the Web

Karl Aberer, Jean Paul Calbimonte Perez

Sensor datasets on the Web are becoming increasingly available, and there is a need for making them discoverable and accessible, so that they can be reused despite their heterogeneity. While RDF and Linked Data provide fundamental principles for sharing da ...

2016

Efficient Distributed Decision Trees for Robust Regression

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo

The availability of massive volumes of data and recent advances in data collection and processing platforms have motivated the development of distributed machine learning algorithms. In numerous real-world applications large datasets are inevitably noisy a ...

2016

A Query Model to Capture Event Pattern Matching in RDF Stream Processing Query Languages

Jean Paul Calbimonte Perez

The current state of the art in RDF Stream Processing (RSP) proposes several models and implementations to combine Semantic Web technologies with Data Stream Management System (DSMS) operators like windows. Meanwhile, only a few solutions combine Semantic ...

Springer Int Publishing Ag2016

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Diabetic patients are dependent on external substances to balance their blood glucose level. In order to control this level, they historically needed to sample a drop a blood from their hand and have it analyzed. Recently, other directions emerged to offer ...

CEUR-WS2016

Querying and reasoning over RDF streams are two increasingly relevant areas in the broader scope of processing structured data on the Web. While RDF Stream Processing (RSP) has focused so far on extending SPARQL for continuous query and event processing, s ...

Springer2016

Processing data streams is increasingly gaining momentum, given the need to process these flows of information in real-time and at Web scale. In this context, RDF Stream Processing (RSP) and Stream Reasoning (SR) have emerged as solutions to combine semant ...

Springer Int Publishing Ag2016

SigCO: Mining Significant Correlations via a Distributed Real-time Computation Engine

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo, Hao Zhuang

The dramatic rise of time-series data produced in a variety of contexts, such as stock markets, mobile sensing, sensor networks, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation systems (e.g., Apach ...

2015

RDF Stream Processing (RSP) bridges the gap between semantic technologies and data stream systems. Although a number of RSP systems have been recently proposed, no RDF streams are actually made publicly available on the Web. To cope with this, RSP engines ...

2015

Events on the Web are increasingly being produced in the form of data streams, and are present in many different scenarios and applications such as health monitoring, environmental sensing or social networks. The heterogeneity of event streams has raised t ...

2015