12062013 ws & bd
TRANSCRIPT
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Charles Huot
[email protected] le 12 juin 2013, T2M
La relation client à l’ère du Web 3.0Web Sémantique & Big Data
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Agenda TEMIS ?
Les bases en 3 min
Exemples & cas d’usages
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Pionnier de l’Enrichissement de Contenu depuis 2000
70
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Structurerles contenus non structuréspour mieux les géreret mieux les valoriser
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Beaucoup plus de données
Vraiment beaucoup plus
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Des puces RFIDpour tracer les vaches
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Des capteurs pour suivre la circulation
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Génome
Décrire les génomes
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Concevoir ensemble
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Parler de soi et des autres
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Une surabondance d’application à gérer!N
um
be
r &
co
mp
lex
ity
of
tec
hn
olo
gie
s/d
ata
so
ur
ce
s
Time Frame
eCommerceSmarter
Planet
eDiscovery
Decision support
Alerting
Watson
Predictions
Historic
Relationship
Detection
Pattern
Detection
Find influencers
Brand management
Climate Modeling
And Prediction
Investment Trend
Detection
Reputationmanagement
Voice of Customer
Gov’t Intelligence
Apps
Log Analysis
Future(Predict)
Ad targeting
Churn detection
Find drug
interactions
Fraud
Detection
Source: IDC, Big Data and the information advantage
Sue Feldman
Sentiment extraction
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Nous ne sommes pas mécontents de la banque XYZ
A l’échelle du verbatimExtraction automatisée des informations
Termes
Pronom Verbe Nom propreArt.Adv.Nég Adjectif
Emetteur Verbe SociétéArt.Modif.Modif. Evaluation
Entités
Nous ne sommes pas mécontents de la banque XYZRelations
Rôles
Attributs
EvaluationPolarité Positive
Intensité -
Sujet Banque XYZ
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Principes d’extraction
Extraction
de relations
Extraction d’entités
Prétraitements linguistiques
Relations Extraction- Une société dans une relation d’acquisition- Un produit bancaire dans une relation d’opinion positive ou négative
Entrée : texte
Sortie : texte annoté
Extraction d’entitésEx.: Entités nommées (Noms de Personnes, Lieux, Sociétés), Entités métier (lexique bancaire), Opinions, etc.
Prétraitements linguistiquesIdentification de la langue, tokenization, segmentation, Analyse morphosyntaxique (POS tagging)
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Anonymisation de l’informationRendre les verbatim anonymes!
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Analyse D’OpinionsDétection des sentiments
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²
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NSA: à l’écoute du monde?
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Non: bienvenue dans la « war room » de Nestlé
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Tableau de bord
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Projet CallSurf (Identification des raisons d’appels et des opinions)
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La télévision et Twitter
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Livres blancs Aproged
E-réputation et B2BFévrier 2013
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L’ALLIANCE BIG DATA20 mars 2013, lancement de :
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L’Alliance Big Data
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www.alliancebigdata.com
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La Charte Ethique & Big Data