The Chair’s Annual Conference

Thursday, October 13th, the Chair held its second annual Conference. After a talk by Gilles Cochevelou, Total’s Chief Digital Officer, a round table debated about the role of start-ups in the big data strategy of larger companies, with the participation of:

  • Benoit Bouffart, Directeur Produits, expérience client et accélération, Voyages-sncf.com
  • Michel Lutz, Group Data Officer, Total
  • Yann Lechelle, COO, SNIPS
  • Arnaud de Moissac, CEO, DCBrain
  • Karim Tekkal, CTO, Safety Line
  • Gilles Cochevelou, Chief Digital Officer, Total

Journée de la Chaire Big Data & Market Insights : Smaller, Faster, Clever

Jeudi 13 octobre 2016 de 16 à 18h
Télécom ParisTech, 46 rue Barrault, 75013 Paris, amphi Thévenin

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Pour sa journée annuelle, la chaire « Big Data & Market Insights » de Télécom ParisTech s’intéresse à la dynamique qui anime l’écosystème Big Data français et en particulier au rôle moteur des start-up. Incubateurs d’entreprises, relation privilégiées, relais d’innovation, les grandes entreprises ont tout à gagner en remettant une partie de leurs développements Big Data entre les mains de structures agiles. Cette année, Gilles Cochevelou, Chief Digital Officer de Total, présentera différents cas d’application de data science aux métiers du groupe.

La plupart des grands groupes français sont aujourd’hui engagés dans leur transformation digitale, notamment autour des données, avec la création de « Data Labs » internes et la nomination de Chief Data Officers. Mais une stratégie d’externalisation de l’innovation se développe en parallèle avec un succès croissant.

Plus agiles, plus créatives, moins contraintes, les start-up sont observées de près par les grands groupes, qui n’hésitent plus à établir des collaborations rapprochées. Certaines entreprises mettent en place leur propre incubateur, d’autres financent des travaux de recherche ou des preuves de concept, certaines fournissent des données ou proposent des locaux et du matériel. Les modalités peuvent être multiples, mais la finalité reste la même : permettre à une idée nouvelle de germer et de se développer, en dehors du cadre formel de l’entreprise.

Difficile, pour les grands acteurs de la banque, du conseil, des transports ou de la grande consommation, d’être sur tous les fronts et d’explorer toutes les possibilités offertes par la science des données, tout en continuant à assurer leurs missions habituelles. Opérant plus rapidement, de façon créative et surtout, sans bouleverser les organisations en place, les start-up ont un rôle à jouer pour aider les grandes entreprises à tirer parti, avec succès, des données relatives à la connaissance client, aux différents métiers, aux réseaux internes (cybersécurité, usine du futur…), à la finance.

Pour sa seconde journée, la Chaire Big Data & Market Insights convie des start-ups du Big Data et de grandes entreprises qui ont choisi de collaborer avec elles, d’externaliser leur force d’innovation afin d’accélérer et d’améliorer les processus d’innovation et de transition numérique : Total, Voyages-sncf.com, SNIPS, DCBrain, Safety Line.

Programme

16h00 Accueil, rappel des objectifs de la Chaire, présentation des travaux et retours d’expérience, par :
•   Talel Abdessalem, Professeur, porteur de la Chaire Big Data & Market Insights
16h30 « Différents cas d’application de data science aux divers métiers de Total »
Exposé de Gilles Cochevelou, Chief Digital Officer de Total
17h00 Table ronde avec :
•   Benoit Bouffart, Directeur Produits, expérience client et accélération, Voyages-sncf.com
•   Michel Lutz, Group Data Officer, Total
•   Yann Lechelle, COO, SNIPS
•   Arnaud de Moissac, CEO, DCBrain
•   Karim Tekkal, CTO, Safety Line
Animée par Yves Vilaginés, journaliste spécialisé en entreprenariat aux Echos
18h00 Échanges avec le public
18h15 Cocktail

 

The Inaugural Paris Summit on Big Data Management

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On Thursday, March 24th 2016 at Telecom ParisTech will take place the Inaugural Paris Summit on Big Data Management.

There has been significant interest in big data techniques and applications in recent years. The goal of this all-day summit is to bring together researchers from the greater Paris area with an interest in big data management, together with invited industry experts, to discuss our collective research strengths and look for opportunities for future collaborations.

This summit will showcase a number of research projects of high relevance and impact, and present a plenary student poster session to broadly cover projects on big data management in the local area. Attendees will also hear from French industry about their data management needs, and pursue further discussion at the social event.

All researchers, industry experts, and practitioners are welcomed to participate, as well as all graduate students who work on related research topics in this area.

Practical details

Presentations will be in English.
The event will take place at Telecom ParisTech, 46 rue Barrault in the 13th arrondissement of Paris.

>> Program and free registration

Journée de la Chaire Big Data & Market Insights le 2 octobre 2015

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Logo-Groupe-BPCE-200px Logo-Deloitte-200px   Logo-Groupe-Rocher-200px

A l’occasion de sa journée annuelle, la chaire « Big Data & Market Insights » de Télécom ParisTech propose une session publique sur le thème de la transformation digitale de l’entreprise par le big data.

Si les technologies Big Data sont souvent mises au service de l’entreprise sur des aspects bien précis, tels que le marketing et la gestion de la relation client, la maintenance prédictive ou la détection de fraude, l’expérience montre que le lancement d’un projet fait souvent boule de neige, entraînant d’autres projets sur des aspects parfois bien différents. La stratégie « data » se développe ainsi et trouve sa légitimité à tous les niveaux de l’entreprise, pouvant devenir un levier majeur de sa transformation.

Cette journée est l’occasion pour la Chaire de présenter au public un aperçu de ses travaux de recherche et de partager des retours d’expérience. Notre invité cette année est Vivek Badrinath, directeur général adjoint en charge du marketing, du digital, de la distribution et des systèmes d’information d’AccorHotels. Il présentera sa vision du Big Data et son rôle dans la transformation digitale du groupe Accor.

Suivra une table ronde sur le thème de la transformation digitale de l’entreprise avec la participation de :

  • Frédéric Burtz, Directeur Technologie et Innovation de la Direction Digital SNCF et Président du comité de pilotage de la Chaire
  • Philippe Poirot, Directeur du développement digital, transformation et qualité du Groupe BPCE
  • Michel Elmaleh, Associé membre du Comité Exécutif et responsable Marketing, Innovation et Offres chez Deloitte France
  • Alain Monzat, Responsable Pilotage et Innovation, Direction Digital IT du Groupe Rocher

Programme

  • 16h00 Accueil, rappel des objectifs de la Chaire, présentation de ses travaux, retours d’expérience
  • 16h30 Exposé de Vivek Badrinath, Directeur général adjoint du groupe AccorHotels « Le Big Data, levier de la transformation d’Accor »
  • 17h00 Table ronde « La transformation digitale de l’entreprise » avec le Groupe BPCE, Deloitte, la SNCF et le Groupe Rocher
  • 17h45 Échanges avec le public
  • 18h00 Cocktail

Informations pratiques

Date et heure : le 2 octobre 2015 de 16h à 18h
Lieu : Télécom ParisTech, 46 rue Barrault, 75013 Paris

Inscriptions closes

ParisTech 1st Data Science Game – May-June 2015

DataScienceGame

ENSAE ParisTech and ParisTech, along with Ensta ParisTech and Telecom ParisTech, invite all data science students from Universities all around the world to participate to the 1st edition of the Data Science Game.

By solving a data driven issue, students will be able to enlighten their data science expertise in a both competitive and friendly spirit.

The competition is supported by two major partners : Google Inc., who will provide the scope and material of the competition, and Capgemini, who will provide an amazing setting for the competition in Paris.

Because data are both major input and output in our connected lives, because data science students are the builders of tomorrow and because we believe that they deserve
to be in the limelight, we encourage you to come and join this first international data science event in Paris. Build a team, handle data provided by our partner, try to answer very challenging questions and demonstrate yours skills among data science students from all around the world.

A two Phases competition:

  • An online non-eliminatory phase from mid-May to mid-June 2015
  • A two-days competition in Paris, the 20th and 21st of June 2015

More information, schedule and registration on www.datasciencegame.com

Real-Time Big Data Stream Analytics – Seminar by ​Albert Bifet on April 30th

​Albert Bifet (http://albertbifet.com) will be invited by the Big Data & Market Insights Chair to give a talk on Thursday, April 30th at the National University of Singapore (NUS) School of Computing, Computer Science department.

data-stream

Big Data is a new term used to identify datasets that we cannot manage with current methodologies or data mining software tools due to their large size and complexity. Big Data mining is the capability of extracting useful information from these large datasets or streams of data. New mining techniques are necessary due to the volume, variability, and velocity, of such data. In this talk, we will focus on advanced techniques in Big Data mining in real time using evolving data stream techniques: using a small amount of time and memory resources, an being able to adapt to changes. We will discuss some advanced state-of-the-art methodologies in stream mining based in the use of adaptive size sliding windows. Finally, we will present the MOA software framework with classification, regression, and frequent pattern methods, and the new Apache SAMOA distributed streaming software.

Albert.Bifet.250x250Dr. Albert Bifet is a Senior Researcher at Huawei. He is the author of a book on Adaptive Stream Mining and Pattern Learning and Mining from Evolving Data Streams. His main research interest is in Learning from Data Streams. He published more than 60 articles. He is serving as Industrial Track co-Chair of ECM-PKDD 2015. He is one of the leaders of MOA and Apache SAMOA software environments for implementing algorithms and running experiments for online learning from evolving data streams. He has been Co-Chair of BigMine (2015, 2014, 2013, 2012), and ACM SAC Data Streams Track (2015, 2014, 2013, 2012).

Groupe BPCE joins the Big Data & Market Insights Chair

Groupe BPCE is joining Groupe Yves Rocher, Voyages-sncf.com and Deloitte as a partner of Télécom ParisTech’s Big Data & Market Insights Research Chair launched with Télécom Business School in December 2013. The Chair’s inter-disciplinary work is geared to improving companies’ knowledge of their clients, to helping them to personalise products and services and to develop techniques for preventing IT fraud and intrusions.

“We are delighted to welcome Groupe BPCE as a partner of the Big Data & Market Insights Chair. Firstly, like our existing partners, Groupe BPCE recognises the major challenges raised by big data and the interest of joining forces with a specialist research team in order to maximise the understanding and use of this data both for the benefit of the Group and of its clients. And secondly, the fact that our partners come from different sectors of activity enables us to enhance our knowledge of the various business issues and needs linked to big data and to develop effective solutions tailored to these individual issues and needs. Groupe BPCE’s entry into the Chair means we can incorporate the needs of the banking and insurance industry into our research work” underlines Talel Abdessalem, the Chair holder.

Download the Press Release (PDF)

Thesis defense: Intelligent Content Acquisition in Web Archiving

On Wednesday, December 17th at Telecom ParisTech, at 2 pm in the Amphi Grenat, Muhammad Faheem will defend his thesis on Intelligent Content Acquisition in Web Archiving. Here is the abstract:

Web sites are dynamic in nature with content and structure changing overtime; many pages on the Web are produced by content management systems (CMSs). Tools currently used by Web archivists to preserve the content of the Web blindly crawl and store Web pages, disregarding the CMS the site is based on and whatever structured content is contained in Web pages. We present in this thesis intelligent systems that crawl the Web in Intelligent manner.

The application-aware helper (AAH), fits into an archiving crawl processing chain to perform intelligent and adaptive crawling of Web applications. Because the AAH is aware of the Web application currently crawled, it is able to refine the list of URLs to process and to extend the archive with semantic information about extracted content. The AAH has introduced a semi-automatic crawling approach that relies on hand-written description of known Web sites.

We also propose a fully-automatic system that does not require any human intervention to crawl the Web pages. We introduce ACEBot (Adaptive Crawler Bot for data Extraction), a structure-driven crawler (fully automatic) that utilizes the inner structure of the Web pages and guides the crawling process based on the importance of their content.

A large part of the information on the Web is hidden behind Web forms (known as the deep Web, or invisible Web, or hidden Web). The above stated systems does not crawl the hidden Web pages. To address this problem, we propose OWET (Open Web Extraction Toolkit) as such a platform, a free, publicly available data extraction framework.

Thesis defense: Large scale recommender systems

On Monday, December 15th, at 2 pm, Modou Gueye will defend his thesis ​at Telecom ParisTech, in room B312. Here is the abstract:

In this thesis, we address the scalability problem of recommender systems. We propose accurate and scalable algorithms.
We first consider the case of matrix factorization techniques in a dynamic context, where new ratings are continuously produced. In such case, it is not possible to have an up to date model, due to the incompressible time needed to compute it. This happens even if a distributed technique is used for
matrix factorization. At least, the ratings produced during the model computation will be missing. Our solution reduces the loss of the quality of the recommendations over time, by introducing some stable biases which track users’ behavior deviation. These biases are continuously updated with the new
ratings, in order to maintain the quality of recommendations at a high level for a longer time.

We also consider the context of online social networks and tag recommendation. We propose an algorithm that takes into account the popularity of the tags and the opinions of the users’ neighborhood. But, unlike common nearest neighbors’ approaches, our algorithm does not rely on a fixed number of neighbors while computing a recommendation. It uses a heuristic that bounds the network traversal in a way that enables computing the recommendations on the fly, with a limited computation cost, while preserving the quality of the recommendations.

Finally, we propose a novel approach that improves the accuracy of the recommendations for top-k algorithms. Instead of a fixed list size, we adjust the number of items to recommend in a way that optimizes the global accuracy of the recommendations. We other words, we optimize the likelihood that all the recommended items will be chosen by the user, and find the best candidate sublist (i.e., the most accurate one) to recommend to the user.

General Objectives

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The Chair is linked to the research activity of two research groups in the Institute Mines-Telecom: the IC2/DBWeb team of Telecom ParisTech and the Management, Marketing and Strategy department of Telecom Ecole de Management. The focus is on massive data management and mining, web information extraction, social networks analysis, data visualization, online marketing and advertising, and business models.

The Big Data and Market Insights Chair aims to:

  • Tackle some key Big Data challenging problems, develop new solutions and tools
  • Promote Data-driven decision-making and marketing solutions, incorporate Big Data into Business Intelligence (BI), predictive analytics tools and marketing strategies
  • Serve as a framework of exchange between the researchers involved in this Chair and the industrial partners. Share concrete problems, data sets, experiments, innovative solutions, etc.

Its purpose is twofold: support and promote a high quality research activity, on the one hand, and heighten awareness of our students to the economic and technological challenges raised by the Big Data, on the other hand.