Search results for "Big data"
showing 10 items of 311 documents
Large Scale Knowledge Matching with Balanced Efficiency-Effectiveness Using LSH Forest
2017
Evolving Knowledge Ecosystems were proposed to approach the Big Data challenge, following the hypothesis that knowledge evolves in a way similar to biological systems. Therefore, the inner working of the knowledge ecosystem can be spotted from natural evolution. An evolving knowledge ecosystem consists of Knowledge Organisms, which form a representation of the knowledge, and the environment in which they reside. The environment consists of contexts, which are composed of so-called knowledge tokens. These tokens are ontological fragments extracted from information tokens, in turn, which originate from the streams of information flowing into the ecosystem. In this article we investigate the u…
DIAMIN: a software library for the distributed analysis of large-scale molecular interaction networks
2022
AbstractBackgroundHuge amounts of molecular interaction data are continuously produced and stored in public databases. Although many bioinformatics tools have been proposed in the literature for their analysis, based on their modeling through different types of biological networks, several problems still remain unsolved when the problem turns on a large scale.ResultsWe propose , that is, a high-level software library to facilitate the development of applications for the efficient analysis of large-scale molecular interaction networks. relies on distributed computing, and it is implemented in Java upon the framework Apache Spark. It delivers a set of functionalities implementing different ta…
Development of a low-cost IoT system to detect and locate lightning strikes
2020
Lightnings are violent natural phenomena and can generate many expenditures, specially when they strike in urban areas. The identification of the concrete geographic area where they strike is of critical importance for emergency services in order to enhance their effectiveness by doing an intensive coverage of the affected area. To achieve this aim, this paper proposes a design, prototype and validation of a distributed network of Internet of Things (IoT) devices to enable detection and location of lightning strikes. The IoT devices are empowered with lightning detection capabilities and are synchronized with the other devices in the sensor network. All of them cooperate within a network th…
Des Translators neue Kleider. Die Translationwirtschaft in Zeiten von Digitalisierung, Datafizierung und Big Data Management
2017
Abstract The Internet of things will influence all professional environments, including translation services. Advances in machine learning, supported by accelerating improvements in computer linguistics, have enabled new systems that can learn from their own experience and will have repercussions on the workflow processes of translators or even put their services at risk in the expected digitalized society. Outsourcing has become a common practice and working in the cloud and in the crowd tend to enable translating on a very low-cost level. Confronted with promising new labels like Industry 4.0 and Work 4.0, professional freelance translators will have to organize themselves as smart office…
Technology-Enhanced Organizational Learning: A Systematic Literature Review
2019
Part 9: Learning and Education; International audience; E-Learning systems are receiving ever increasing attention in, academia, businesses as well as in public administrations. Managers and employee who need efficient forms of training as well as learning flow within the organization, do not have to gather in a place at the same time, or to travel far away for attending courses. Contemporary affordances of e-learning systems allow them to perform different jobs or tasks for training courses according to their own scheduling, as well as collaborate and share knowledge and experiences that results rich learning flow within the organization. The purpose of this article is to provide a systema…
La littérature en numérique. À propos de : Franco Moretti (dir.), La littérature au laboratoire, Ithaque
2017
International audience; Qu’apportent les big data à notre interprétation de Hugo, Balzac ou Flaubert ? Beaucoup, parce que les humanités numériques, loin d’accumuler mécaniquement des données sur les textes littéraires, changent notre rapport aux œuvres et notre manière de les lire.
Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method
2020
The Superposing Significant Interaction Rules (SSIR) method is a combinatorial procedure that deals with symbolic descriptors of samples. It is able to rank the series of samples when those items are classified into two classes. The method selects preferential descriptors and, with them, generates rules that make up the rank by means of a simple voting procedure. Here, two application examples are provided. In both cases, binary or multilevel strings encoding gene expressions are considered as descriptors. It is shown how the SSIR procedure is useful for ranking the series of patient transcription data to diagnose two types of cancer (leukemia and prostate cancer) obtaining Area Under Recei…
Extracting business information from graphs: An eye tracking experiment
2016
Information graphics are visualizations that convey information about data trends and distributions. Data visualization and the application of graphs is increasingly important in business decision making, for instance, in big data analysis. However, relatively little information exists about how people extract information from graphs and how the framing of the graphic design defines may ‘nudge’ and bias decision making. As a contribution to fill this gap, this study applies the methodology of experimental economics to the analysis of graph reading and processing to extract underlying information. Specifically, the study presents the results of an experiment whose baseline treatment includes…
Locality-Sensitive Hashing for Massive String-Based Ontology Matching
2014
This paper reports initial research results related to the use of locality-sensitive hashing (LSH) for string-based matching of big ontologies. Two ways of transforming the matching problem into a LSH problem are proposed and experimental results are reported. The performed experiments show that using LSH for ontology matching could lead to a very fast matching process. The quality of the alignment achieved in these experiments is comparable to state-of-the-art matchers, but much faster. Further research is needed to find out whether the use of different metrics or specific hardware would improve the results. peerReviewed
Predicting disease outbreaks: evaluating measles infection with Wikipedia Trends.
2019
The primary aim of this study was to evaluate the temporal correlation between Wikitrends and conventional surveillance data generated for measles infection reported by bulletin of Istituto Superiore di Sanità (ISS). The reported cases of measles were selected from July 2015 to October 2018. Wikipedia Trends was used to assess how many times a specific page was read by users, data were extracted as daily data and aggregated on a weekly and monthly basis. The following data were extracted: number of views by users from 1 July 2015 to 31 October 2018 of the Morbillo, Vaccinazione del Morbillo, Vaccinazione MPR and Macchie di Koplik pages (Measles, Measles Vaccination, MPR Vaccination and Kopl…