Search results for "Big data"
showing 10 items of 311 documents
Keynote speakers: Benefits and drawbacks of the BigData era
2017
We have voluntarily surrendered our private data to BigData companies like Google and FaceBook in hope that our data there will be safe and will be used only for ethical machine learning purposes to further advance artificial intelligence capabilities we already use daily: smart search, machine translation, speech recognition, guessing our interests etc. But alongside these positive BigData uses, unexpectedly the world was recently astounded by the success of the DataScience killer-application: microtargeting, discussed in this presentation.
A novel policy-driven reversible anonymisation scheme for XML-based services
2015
Author's version of an article in the journal: Information Systems. Also available from the publisher at: http://dx.doi.org/10.1016/j.is.2014.05.007 This paper proposes a reversible anonymisation scheme for XML messages that supports fine-grained enforcement of XACML-based privacy policies. Reversible anonymisation means that information in XML messages is anonymised, however the information required to reverse the anonymisation is cryptographically protected in the messages. The policy can control access down to octet ranges of individual elements or attributes in XML messages. The reversible anonymisation protocol effectively implements a multi-level privacy and security based approach, s…
A Review on Applications of Big Data for Disaster Management
2017
International audience; The term " disaster management " comprises both natural and man-made disasters. Highly pervaded with various types of sensors, our environment generates large amounts of data. Thus, big data applications in the field of disaster management should adopt a modular view, going from a component to nation scale. Current research trends mainly aim at integrating component, building, neighborhood and city levels, neglecting the region level for managing disasters. Current research on big data mainly address smart buildings and smart grids, notably in the following areas: energy waste management, prediction and planning of power generation needs, improved comfort, usability …
Adaptive Learning Process for the Evolution of Ontology-Described Classification Model in Big Data Context
2016
International audience; One of the biggest challenges in Big Data is to exploit value from large volumes of variable and changing data. For this, one must focus on analyzing the data in these Big Data sources and classify the data items according to a domain model (e.g. an ontology). To automatically classify unstructured text documents according to an ontology, a hierarchical multi-label classification process called Semantic HMC was proposed. This process uses ontologies to describe the classification model. To prevent cold start and user overload, the classification process automatically learns the ontology-described classification model from a very large set of unstructured text documen…
Privacy in Big Data
2016
International audience
A Neural Network Meta-Model and its Application for Manufacturing
2015
International audience; Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to increase a manufacturer's competitive advantage through improved sustainability, productivity, and flexibility of their operations. Manufacturers, as well as other industries, have successfully applied a promising statistical learning technique, called neural networks (NNs), to extract meaningful information from large data sets, so called big data. However, the application of NN to manufacturing problems remains limited because it involves the specialized skills of a data scientist. This paper introduces an appr…
Semantic User Profiling for Digital Advertising
2015
International audience; With the emergence of real-time distribution of online advertising space (“real-time bidding”), user profiling from web navigation traces becomes crucial. Indeed, it allows online advertisers to target customers without interfering with their activities. Current techniques apply traditional methods as statistics and machine learning, but suffer from their limitations. As an answer, the proposed approach aims to develop and evaluate a semantic-based user profiling system for digital advertising.
Customizing Semantic Profiling for Digital Advertising
2014
International audience; Personalization is the new magic buzzword of application development. To make the complexity of today's application functionalities and information spaces "digestible", customization has become the new go-to technique. But while those technologies aim to ease the consumption of media for their users, they suffer from the same problematic: in the age of Big Data, applications have to cope with a conundrum of heterogeneous information sources that have to be perceived, processed and interpreted. Researchers tend to aim for a maximum degree of integration to create the perfect, all-embracing personalization. The results are wide-range, but overly complex systems that su…
Ontology-based Integration of Web Navigation for Dynamic User Profiling
2015
The development of technology for handling information on a Big Data-scale is a buzzing topic of current research. Indeed, improved techniques for knowledge discovery are crucial for scientific and economic exploitation of large-scale raw data. In research collaboration with an industrial actor, we explore the applicability of ontology-based knowledge extraction and representation for today's biggest source of large-scale data, the Web. The goal is to develop a profiling application, based on the implicit information that every user leaves while navigating the online, with the goal to identify and model preferences and interests in a detailed user profile. This includes the identification o…
Leveraging the benefits of big data with fast data for effective and efficient cybersecurity analytics systems : A robust optimisation approach
2020
In recent times, major cybersecurity breaches and cyber fraud within the public and private sectors are making international headlines. Majority of organisations are facing cybersecurity adversity and advanced threats. On the one hand, we have asynchronous cybersecurity practices, many standards and frameworks to consider while on the other hand, we have to deal and secure our organisations against cyber-criminals, organised hacktivists, insider threats, hackers and nation-states with malafide intentions. The Center for Cyber Safety and Education's Global Information Security Workforce Study (GISWS) confirms that globally we are not only loosing but also backpedalling against threats and ri…