BigDataFr recommande : La France se prépare au futur de son industrie […] Robots et capteurs, simulation et connectivité, intégration de la culture digitale et bouleversement des modèles économiques, l’industrie se transforme en profondeur. Cette mutation est organisationnelle autant que technologique. Toutes les entreprises françaises n’ont pas encore pris conscience des changements profonds qui nécessitent […]
Technologies
[arXiv] BigDataFr recommends: A European research roadmap for optimizing societal impact of big data on environment and energy efficiency
BigDataFr recommends: A European research roadmap for optimizing societal impact of big data on environment and energy efficiency […] We present a roadmap to guide European research efforts towards a socially responsible big data economy that maximizes the positive impact of big data in environment and energy efficiency. The goal of the roadmap is to […]
[HAL] BigDataFr recommends: Stream-based Reasoning for IoT Applications – Proposal of Architecture and Analysis of Challenges
BigDataFr recommends: Stream-based Reasoning for IoT Applications – Proposal of Architecture and Analysis of Challenges Abstract […] As distributed IoT applications become larger and more complex, the pure processing of raw sensor and actuation data streams becomes impractical. Instead, data streams must be fused into tangible facts and these pieces of information must be combined […]
[La Tribune] BigDataFr recommande : Data marketing : la startup Mediarithmics lève 3 millions d’euros pour s’internationaliser
BigDataFr recommande : Data marketing : la startup Mediarithmics lève 3 millions d’euros pour s’internationaliser […] Pas facile de se faire un nom dans un secteur, le marketing personnalisé, dominé par des géants américains tels que SAP, Oracle, IBM ou encore HP. Pourtant, la startup française Mediarithmics a décidé de se lancer dans le bain. […]
[Dataconomy] BigDataFr recommends: Trends Shaping Machine Learning in 2017
BigDataFr recommends: Trends Shaping Machine Learning in 2017 […] Technologies in the field of data science are progressing at an exponential rate. The introduction of Machine Learning has revolutionized the world of data science by enabling computers to classify and comprehend large data sets. Another important innovation which has changed the paradigm of the world […]
[JDN] BigDataFr recommends: L’or noir du numérique, le big data nous livre ses secrets
BigDataFr recommande: L’or noir du numérique, le big data nous livre ses secrets r […] Ce qu’on appelle communément « l’or noir du numérique » demeure une matière encore difficile à exploiter pleinement par les établissements financiers. Amenée à augmenter de manière exponentielle dans les prochaines années, cette masse d’information est continuellement alimentée par le multimédia, l’omniprésence […]
[ZDNet] BigDataFr recommande: Report shows that AI is more important to IoT than big data insights
BigDataFr recommends: Report shows that AI is more important to IoT than big data insights The problem with big data and business intelligence software is that it is reactionary and static. A recent survey from data analysis provider GlobalData showed that IoT professionals still have a heavy reliance on traditional business intelligence (BI) software. Around […]
[arXiv] BigDataFr recommends: Massively-Parallel Feature Selection for Big Data
BigDataFr recommends: Massively-Parallel Feature Selection for Big Data […] We present the Parallel, Forward-Backward with Pruning (PFBP) algorithm for feature selection (FS) in Big Data settings (high dimensionality and/or sample size). To tackle the challenges of Big Data FS PFBP partitions the data matrix both in terms of rows (samples, training examples) as well as […]
[Datanami] BigDataFr recommends: Big Data Analytics Flashes a ‘Red Alert’ on Human Trafficking in India
BigDataFr recommends: Big Data Analytics Flashes a ‘Red Alert’ on Human Trafficking in India […] The statistics are terrifying: Every three minutes, a young Indian girl is abducted into sex slavery — often with the consent of her parents, as horrible as that sounds. Now, with the help of Australian analytics firm Quantium, a project […]
[HAL] BigDataFr recommends: Computing Dense Tensor Decompositions with Optimal Dimension Trees
BigDataFr recommends: Computing Dense Tensor Decompositions with Optimal Dimension Trees Abstract […] Dense tensor decompositions have been widely used in many signal processing problems including analyzing speech signals, identifying the localization of signal sources, and many other communication applications. Computing these decompositions poses major computational challenges for big datasets emerging in these domains. CANDECOMP/PARAFAC (CP) […]