Big Continuous Data: Dealing with Velocity by Composing Event Streams

Vargas-Solar, Genoveva; Espinosa-Oviedo, Javier A.; Zechinelli-Martini, José-Luis

doi:10.1007/978-3-319-27763-9_1

Cited by 5 publications

(3 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, we did not carry out a separate expert survey. The value determination for the individual big data analytics characteristics within the survey are based on previous academic findings (Schön 2016;Van Altena et al 2016;Vargas-Solar et al 2016;Géczy 2014) and an expert survey according to Seufert (2016). Furthermore, due to the lack of a complete reflectivity of the theoretical constructs, the measurement concept was uniformly defined to be formative.…”

Section: Construct Operationalizationmentioning

confidence: 99%

Big data analytics in sustainability reports: an analysis based on the perceived credibility of corporate published information

Wanner

Janiesch

2019

Bus Res

View full text Add to dashboard Cite

The credibility of sustainability reports has been the subject of scientific research for several years. The problem is often referred to as the so-called credibility gap, which is based on information asymmetries. The situation is further complicated by the limited rationality of human action as improvements to reports do not necessarily translate into credibility gains. Research has proposed and extracted several methods to overcome the issue. Hitherto, most approaches to solve the problem focused on marketing-oriented approaches. This work takes a new approach and explores the extent to which information technology can increase credibility using the potential of big data analytics. We base our research on the relationship of the quality of information and on the perception of objective truth as postulated in the Habermas Theory of Communicative Action. We use the forecastoriented Partial Least Squares Methodology for the review of hypotheses extracted from literature and expert surveys. The result confirms potential of the criteria of volume and veracity while velocity and variety do not yield comparable potential concerning sustainability reporting.

show abstract

Section: Construct Operationalizationmentioning

confidence: 99%

Big data analytics in sustainability reports: an analysis based on the perceived credibility of corporate published information

Wanner

Janiesch

2019

Bus Res

View full text Add to dashboard Cite

show abstract

“…Data started to acquire "new" properties (more volume, velocity, variety) and with them emerged the need for building huge curated data collections out of data produced by different devices, under different conditions for later analysis (Adiba, Castrejón, Espinosa-Oviedo, Vargas-Solar, & Zechinelli-Martini, 2015;Labrinidis & Jagadish, 2012). The challenge was to collect data continuously (Ma, Wang, & Chu, 2013) and to ensure that collections could be used to perform analysis (Vargas-Solar, Espinosa-Oviedo, & Zechinelli-Martini, 2016): statistical, data mining, machine learning, deep learning and so on (Shah & Sheth, 1999). Works and tools include collection, cleaning, profiling and distributed storage (Barnaghi, Sheth, & Henson, 2013).…”

Section: Related Workmentioning

confidence: 99%

Analyzing Digital Politics - Challenges and Experiments in a Dual Perspective

Castel¹,

Vargas-Solar²,

Espinosa-Oviedo³

2020

ROISI

Self Cite

View full text Add to dashboard Cite

Au cours de ces dix dernières années, les réseaux sociaux sont devenus un élément central de la vie politique. Cependant, pour ceux qui s'intéressent à l'analyse des stratégies de communication des partis et des candidats en période électorale, les conséquences de l'introduction d'Internet dans la sphère politique ont été mitigées. En effet, si la recherche, la consultation et l'archivage de documents originaux relatifs à une campagne spécifique sont devenus plus faciles, plus rapides et réalisables à plus grande échelle, ouvrant ainsi un eldorado prometteur pour la recherche dans ce domaine, l'étude des campagnes en ligne a aussi inévitablement introduit de nouveaux défis techniques, méthodologiques et juridiques qui se sont révélés de plus en plus complexes à résoudre pour les chercheurs en sciences humaines et sociales. Le présent document propose donc de fournir un retour d'expérience ainsi qu'une validation expérimentale d'un projet pluridisciplinaire consacré à l'analyse comparative des campagnes politiques sur les réseaux sociaux à l'approche des élections au Parlement européen de 2014 en France et au Royaume-Uni. En plus d'observations formulées du point de vue des humanités sur les problématiques liées à un tel projet, le présent document présente des résultats expérimentaux concernant trois des phases du cycle de vie de la collecte des données : la collecte, le nettoyage et le stockage. Il en résulte une base de données prête à être analysées selon différents angles afin d'aider à traiter le sujet abordé en sciences politiques. ABSTRACT. Social networks have become in the last decade central to political life. However, to those interested in analysing the communication strategies of parties and candidates at election time, the introduction of the Internet into the political sphere has proved a mixed blessing. Indeed, while retrieving, consulting, and archiving original documents pertaining to a specific campaign have become easier, faster, and achievable on a larger scale, thus opening up a promising El Dorado for research in this area, studying online campaigns has also inevitably introduced new technical, methodological and legal challenges which have turned out to be increasingly complex for academics in the humanities and social sciences to solve on their own. This paper therefore proposes to provide feedback on experience and experimental validation from a multidisciplinary project called POLIWEB devoted to the comparative analysis of political campaigns on social media in the run up to the 2014 elections to the European Parliament in France and in the United Kingdom. Together with observations from a humanities' perspective on issues related to such a project, this paper also presents experimental results concerning three of the data collection life cycle phases: collection, cleaning, and storage. The outcome is a data collection ready to be analysed for various purposes meant to address the political science topic under consideration. MOTS-CLÉS. Politique, campagnes, élections, base de données, m...

show abstract

“…In this work, the CT scan image is the input to the classifier system and the output is either the person who has COVID-19 or does not. CNN is a neural network type that is very efficient in extracting image features and building classifier models that can be trained and tested on the features [4,5]. A decision matrix integrating a combination of 10 assessment parameters and 12 diagnostic models for COVID-19 was devised in another work.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Convolutional Neural Network for COVID-19 Detection

Al-Janabi¹,

Al‐Khateeb²,

Mahmood³

et al. 2021

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

The recent novel coronavirus (COVID-19, as the World Health Organization has called it) has proven to be a source of risk for global public health. The virus, which causes an acute respiratory disease in persons, spreads rapidly and is now threatening more than 150 countries around the world. One of the essential procedures that patients with COVID-19 need is an accurate and rapid screening process. In this research, utilizing the features of deep learning methods, we present a method for detecting COVID-19 and a screening model that uses pulmonary computed tomography images to differentiate COVID-19 pneumonia from healthy cases. In this study, 256 cases (128 COVID-19, 128 normal) are used to detect COVID-19 early. Real cases of 51 external COVID-19 images are also taken from Iraqi hospitals and used to validate the proposed method. Segmentations of the lung and infection fields are retrieved from the images during preprocessing. The total accuracy obtained from the results is 98.70%, indicating the success of the designed model.

show abstract

Big Continuous Data: Dealing with Velocity by Composing Event Streams

Cited by 5 publications

References 42 publications

Big data analytics in sustainability reports: an analysis based on the perceived credibility of corporate published information

Big data analytics in sustainability reports: an analysis based on the perceived credibility of corporate published information

Analyzing Digital Politics - Challenges and Experiments in a Dual Perspective

An Enhanced Convolutional Neural Network for COVID-19 Detection

Contact Info

Product

Resources

About