Search results for "Big data"
showing 10 items of 311 documents
Change Discovery in Heterogeneous Data Sources of a Data Warehouse
2020
Data warehouses have been used to analyze data stored in relational databases for several decades. However, over time, data that are employed in the decision-making process have become so enormous and heterogeneous that traditional data warehousing solutions have become unusable. Therefore, new big data technologies have emerged to deal with large volumes of data. The problem of structural evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. In this paper, we propose an approach to change discovery in data sources of a data warehouse utilized to analyze big data. Our solution incorporates an architecture that allows t…
OnMLM: An Online Formulation for the Minimal Learning Machine
2019
Minimal Learning Machine (MLM) is a nonlinear learning algorithm designed to work on both classification and regression tasks. In its original formulation, MLM builds a linear mapping between distance matrices in the input and output spaces using the Ordinary Least Squares (OLS) algorithm. Although the OLS algorithm is a very efficient choice, when it comes to applications in big data and streams of data, online learning is more scalable and thus applicable. In that regard, our objective of this work is to propose an online version of the MLM. The Online Minimal Learning Machine (OnMLM), a new MLM-based formulation capable of online and incremental learning. The achievements of OnMLM in our…
A comprehensive survey of multi-view video summarization
2021
[EN] There has been an exponential growth in the amount of visual data on a daily basis acquired from single or multi-view surveillance camera networks. This massive amount of data requires efficient mechanisms such as video summarization to ensure that only significant data are reported and the redundancy is reduced. Multi-view video summarization (MVS) is a less redundant and more concise way of providing information from the video content of all the cameras in the form of either keyframes or video segments. This paper presents an overview of the existing strategies proposed for MVS, including their advantages and drawbacks. Our survey covers the genericsteps in MVS, such as the pre-proce…
On Internet of Things Programming Models
2016
In this paper, we present the review of existing and proposed programming models for Internet of Things (IoT) applications. The requests by the economy and the development of computer technologies (e.g., cloud-based models) have led to an increase in large-scale projects in the IoT area. The large-scale IoT systems should be able to integrate diverse types of IoT devices and support big data analytics. And, of course, they should be developed and updated at a reasonable cost and within a reasonable time. Due to the complexity, scale, and diversity of IoT systems, programming for IoT applications is a great challenge. And this challenge requires programming models and development systems at …
Towards a validated definition of the clinical transition to secondary progressive multiple sclerosis: A study from the Italian MS Register.
2022
Background: Definitions for reliable identification of transition from relapsing-remitting multiple sclerosis (MS) to secondary progressive (SP)MS in clinical cohorts are not available. Objectives: To compare diagnostic performances of two different data-driven SPMS definitions. Methods: Data-driven SPMS definitions based on a version of Lorscheider’s algorithm (DDA) and on the EXPAND trial inclusion criteria were compared, using the neurologist’s definition (ND) as gold standard, in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), Akaike information criterion (AIC) and area under the curve (AUC). Results: A cohort of 10,240 MS patients wi…
Transition to secondary progression in relapsing-onset multiple sclerosis: Definitions and risk factors
2021
Background: No uniform criteria for a sensitive identification of the transition from relapsing–remitting multiple sclerosis (MS) to secondary-progressive multiple sclerosis (SPMS) are available. Objective: To compare risk factors of SPMS using two definitions: one based on the neurologist judgment (ND) and an objective data-driven algorithm (DDA). Methods: Relapsing-onset MS patients ( n = 19,318) were extracted from the Italian MS Registry. Risk factors for SPMS and for reaching irreversible Expanded Disability Status Scale (EDSS) 6.0, after SP transition, were estimated using multivariable Cox regression models. Results: SPMS identified by the DDA ( n = 2343, 12.1%) were older, more disa…
Big Data in Emergency Management: Exploitation Techniques for Social and Mobile Data
2020
The Internet of Things, crowdsourcing, social media, public authorities, and other sources generate bigger and bigger data sets. Big and open data offers many benefits for emergency management, but also pose new challenges. This chapter will review the sources of big data and their characteristics. We then discuss potential benefits of big data for emergency management along with the technological and societal challenges it poses. We review central technologies for big-data storage and processing in general, before presenting the Spark big-data engine in more detail. Finally, we review ethical and societal threats that big data pose.
Algorithms, artificial intelligence and automated decisions concerning workers and the risks of discrimination: the necessary collective governance o…
2019
Big data, algorithms and artificial intelligence now allow employers to process information on their employees and potential employees in a far more efficient manner and at a much lower cost than in the past. This makes it possible to profile workers automatically and even allows technology itself to replace human resources personnel in making decisions that have legal effects on employees (recruitment, promotion, dismissals, etc.). This entails great risks of worker discrimination and defencelessness, with workers unaware of the reasons underlying any such decision. This article analyses the protections established in the EU General Data Protection Regulation (GDPR) for safeguarding emplo…
Big data and HR analytics in the digital era
2019
Purpose The purpose of this paper is to focus on how the HR function takes advantage of human resource analytics (HRA), including big data (BD), and discuss factors hindering HRA and data utilization. Moreover, the authors discuss the implications of the HRA-induced role transformation of the human resource (HR) function. Design/methodology/approach This is an explorative case study based on qualitative interviews in nine leading Finnish companies. Findings The results indicate that both technical and human obstacles, operating with very basic HR processes and traditional information systems and poor data quality, hinder adoption of advanced HRA. This, combined with lacking skills in analy…
Google matrix analysis of worldwide football mercato
2018
[EN] The worldwide football transfer market is analyzed as a directed complex network: the football clubs are the network nodes and the directed edges are weighted by the total amount of money transferred from a club to another. The Google matrix description allows to treat every club independently of their richness and allows to measure for a given club the efficiency of player sales and player acquisitions. The PageRank algorithm, developed initially for the World Wide Web, naturally characterizes the ability of a club to import players. The CheiRank algorithm, also developed to analyze large scale directed complex networks, characterizes the ability of a club to export players. The analy…