tomás pariente lobo – atos spain final review meeting, luxembourg. 20 november 2012 conclusion
TRANSCRIPT
Tomás Pariente Lobo – Atos Spain
Final Review Meeting, Luxembourg. 20 November 2012
Conclusion
Overall Project Objectives
Technical Impact Near real-time and scalable financial
unstructured data acquisition, extraction, analysis, integration, and visualization pipeline
Well grounded, deep semantic sentiment analysis (using financial and knowledge representation theories)
Advanced financial decision support models based on high-level features
Advanced real-time visualization techniques
Real-world use cases using the underlying FIRST infrastructure
Open source and commercial versions to maximize business possibilities.
Increase the ability to exploit very large financial information spaces for citizens and professionals.
Decrease information asymmetry and increase market transparency at the financial markets and thus contribute to making such markets more trustworthy.
Increase the competitiveness of European financial service providers and institutions
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Project Achievements
Technical Near real-time and scalable financial
unstructured data acquisition, extraction, analysis, integration, and visualization pipeline
Well grounded, deep semantic sentiment analysis (using financial and knowledge representation theories)
Advanced financial decision support models based on high-level features
Advanced real-time visualization techniques
Real-world use cases using the underlying FIRST infrastructure
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3,159 RSS feeds
15 million unique documents collected
Project Achievements
Technical Near real-time and scalable financial
unstructured data acquisition, extraction, analysis, integration, and visualization pipeline
Well grounded, deep semantic sentiment analysis (using financial and knowledge representation theories)
Advanced financial decision support models based on high-level features
Advanced real-time visualization techniques
Real-world use cases using the underlying FIRST infrastructure
Hybrid Fuzzy
sentiment
Corpus
Crisp sentime
nt
5 degrees of positive & negative
sentiment
Labeled by domain uc#
experts
Knowledge-based
approach
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Project Achievements
Technical Near real-time and scalable financial
unstructured data acquisition, extraction, analysis, integration, and visualization pipeline
Well grounded, deep semantic sentiment analysis (using financial and knowledge representation theories)
Advanced financial decision support models based on high-level features
Advanced real-time visualization techniques
Real-world use cases using the underlying FIRST infrastructure
Enhanced Financial Decision Support
Qualitative Modeling
Machine Learning
Techniques
Visualization Techniques
Price Vola P&L Assess
high low good unacc
med high good unacc
med Med good acc
low Low acc acc
low Low good good 5
Quantitative models for doc. categorization, P&D detection, and Twitter sentiment classification
Qualitative models for RIM and P&D
Project Achievements
Technical
Gauge
Canyon
Confidence
Sentiment with volume
…6
Near real-time and scalable financial unstructured data acquisition, extraction, analysis, integration, and visualization pipeline
Well grounded, deep semantic sentiment analysis (using financial and knowledge representation theories)
Advanced financial decision support models based on high-level features
Advanced real-time visualization techniques
Real-world use cases using the underlying FIRST infrastructure
Project Achievements
Technical Near real-time and scalable financial
unstructured data acquisition, extraction, analysis, integration, and visualization pipeline
Well grounded, deep semantic sentiment analysis (using financial and knowledge representation theories)
Advanced financial decision support models based on high-level features
Advanced real-time visualization techniques
Real-world use cases using the underlying FIRST infrastructure
Market SurveillancePrototype for capital market surveillancePositive end-user feedback
Reputational Risk
RIM modelWeb interface
Positive experts
feedback
Retail BrokerageAdditional indicators
(sentiment & tweet volume)
Positive customer feedback
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Qualitative Quantitative Visualization
Project Achievements
Impact Open source and commercial
versions to maximize business possibilities.
Increase the ability to exploit very large financial information spaces for citizens and professionals.
Decrease information asymmetry and increase market transparency at the financial markets and thus contribute to making such markets more trustworthy.
Increase the competitiveness of European financial service providers and institutions
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Proprietary
https://github.com/project-first
External usage / commercial
Project Achievements
Impact Open source and commercial
versions to maximize business possibilities.
Increase the ability to exploit very large financial information spaces for citizens and professionals.
Decrease information asymmetry and increase market transparency at the financial markets and thus contribute to making such markets more trustworthy.
Increase the competitiveness of European financial service providers and institutions
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• Large datasets of:
• Financial Webs, blogs, news, etc.
• Financial Tweets
social
• Several financial scenarios explored
• FIRST OS infrastructure delivered
professionals
• Glassbox model• Open Sentify portal
• Downloadable Datasets
citizens
Project Achievements
Impact Open source and commercial
versions to maximize business possibilities.
Increase the ability to exploit very large financial information spaces for citizens and professionals.
Decrease information asymmetry and increase market transparency at the financial markets and thus contribute to making such markets more trustworthy.
Increase the competitiveness of European financial service providers and institutions
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Document
sentencesObjectsFeatures
Sentiment
Drill down X
The glassbox model
Use cases
Pump & DumpMarket soundingReputational riskRetail brokerage
Future scenariosSovereign Debt
Market abuseDataset usage…
Project Achievements
Impact Open source and commercial
versions to maximize business possibilities.
Increase the ability to exploit very large financial information spaces for citizens and professionals.
Decrease information asymmetry and increase market transparency at the financial markets and thus contribute to making such markets more trustworthy.
Increase the competitiveness of European financial service providers and institutions
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Competitive advantage for financial services providers
Customer expectatio
ns
New scenario
s / usage
Open SourceSpin-off
Competitive advantage for usecase providers
Good technical work
High potential impact
Future work
Thanks
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