Search results for "big data."
showing 10 items of 310 documents
Mining customer requirements from online reviews: A product improvement perspective
2016
We propose a filtering model to predict helpfulness of reviews for product design.We provide a way to use the KANO model based on online reviews.We explore how to obtain insights from Big Data through knowledge-based view. Big data commerce has become an e-commerce trend. Learning how to extract valuable and real time insights from big data to drive smarter and more profitable business decisions is a main task of big data commerce. Using online reviews as an example, manufacturers have come to value how to select helpful online reviews and what can be learned from online reviews for new product development. In this research, we first proposed an automatic filtering model to predict the help…
The efficiency of LiDAR HMLS scanning in monitoring forest structure parameters: implications for sustainable forest management
2022
PurposeThis article aims to compare the LiDAR handheld mobile laser scanner (HMLS) scans with traditional survey methods, as the tree gauge and the hypsometer, to study the efficiency of the new technology in relation to the accuracy of structural forest attributes estimation useful to support a sustainable forest management.Design/methodology/approachA case study was carried out in a high forest located in Tuscany (Italy), by considering 5 forest types, in 20 different survey plots. A comparative analysis between two survey methods will be shown in order to verify the potential limits and the viability of the LiDAR HMLS in the forest field.FindingsThis research demonstrates that LiDAR HMLS…
Open data, big data : quel renouveau du raisonnement cartographique ?
2017
International audience; Le mouvement d’open data, qui permet l’accès gratuit à un grand nombre de données spatiales ou démographiques, associé au développement d’outils de cartographie ou de visualisation libres (SIG, programme), a permis l’augmentation de la production de cartes. Seulement, l’automatisation des traitements permise par ces outils tend à gommer le raisonnement cartographique et peut conduire à des erreurs de construction cartographique, d’autant plus que la phase d’analyse des données peut s’avérer de plus en plus complexe dans un contexte de big data (en tant que données massives, peu structurées et désagrégées). Le raisonnement cartographique est le processus menant d’une …
Estimation of total electricity consumption curves of small areas by sampling in a finite population
2016
International audience; Many studies carried out in the French electricity company EDF are based on the analysis of the total electricity consumption curves of groups of customers. These aggregated electricity consumption curves are estimated by using samples of thousands of curves measured at a small time step and collected according to a sampling design. Small area estimation is very usual in survey sampling. It is often addressed by using implicit or explicit domain models between the interest variable and the auxiliary variables. The goal here is to estimate totals of electricity consumption curves over domains or areas. Three approaches are compared: the rst one consists in modeling th…
Smart transportation as a driver of transition: Big data management, behavioral change and the shift to automated vehicles
2017
Background: Smart mobility can contribute to the design of “Smart cities” to answer users’ requests in terms of transport network efficiency, environmental and social sustainability. Focusing on urban smart mobility issues, the most important aspects are the presence of a connected transportation system, the availability of its information in the arrangement of digital data and the possibility to rapidly communicate it in an effective way to the citizens, urban transportation stakeholders andlocal authorities. Therefore, the challenges for the new era of mobility behavior would range from the effort of big data management and the need to shape the innovation of traveler demand to the change…
A big data approach for sequences indexing on the cloud via burrows wheeler transform
2020
Indexing sequence data is important in the context of Precision Medicine, where large amounts of "omics"data have to be daily collected and analyzed in order to categorize patients and identify the most effective therapies. Here we propose an algorithm for the computation of Burrows Wheeler transform relying on Big Data technologies, i.e., Apache Spark and Hadoop. Our approach is the first that distributes the index computation and not only the input dataset, allowing to fully benefit of the available cloud resources. Copyright © 2020 for this paper by its authors.
IL REGISTRO REGIONALE DELLE CRONICITÀ: NUOVI ALGORITMI PER LA VALUTAZIONE DEI PROFILI DI CONSUMI PER CATEGORIE DIAGNOSTICHE IN SICILIA
2013
Introduzione. Conoscere la prevalenza di una malattia cronica è essenziale per una corretta programmazione delle risorse economiche e umane necessarie per l’implementazione delle strategie preventive e terapeutiche. La Base Dati degli Assistibili (BDA), sviluppata nell’ambito del Piano Operativo di Assistenza Tecnica alle Regioni dell’Obiettivo Convergenza (POAT) cui la Regione Sicilia partecipa attivamente, consente dianalizzare in modo integrato le informazioni provenienti dai diversi flussi informativi che la costituiscono. Obiettivi. Costituire un registro regionale delle cronicità in Sicilia, al fine di valutare i profili di consumi per categorie diagnostiche e stimarne i relativi cari…
Entre big data et big brother
2017
Chap. 40; National audience
Development of Applications for Interactive and Reproducible Research: a Case Study
2016
For a proper understanding of the organization and regulation of gene expression, the computational analysis is an essential component of the scientific workflow, and this is particularly true in the fields of biostatistics and bioinformatics. Interactivity and reproducibility are two highly relevant features to consider when adopting or designing a tool, and often they can not be provided simultaneously.In this work, we address the issue of developing a framework that can provide interactive analysis, in order to allow experimentalists to fully exploit advanced software tools, as well as reproducibility as an internal validation of the analysis steps, by providing the underlying code and d…
Protein Interaction Networks and Disease: Highlights of the 3rd Challenges in Computational Biology Meeting
2017
Cellular functions are managed by a complex network of protein interactions, the malfunction of which may derive in disease phenotypes. In spite of the incompleteness and noise present in our current protein interaction maps, computational biologists are making strenuous efforts to extract knowledge from these intricate networks and, through their integration with other types of biological data, expedite the development of novel and more effective treatments against human disorders. The 3rd Challenges in Computational Biology meeting revolved around the Protein Interaction Networks and Disease subject, bringing expert network biologists to the city of Mainz, Germany to debate the current st…