automating understanding strata spring 2012 final
TRANSCRIPT
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Automated UnderstandingThe Next Evolution of Big Data Analytic
Fo
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What do Alice & The USPTO have in com
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What is Understanding?
Awareness
Reading
Relating
Comprehending
Inference
Interpreta
Prediction
Creation
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UNDERSTANDING = WHAT I DO WITHMY DATA
Big Data? What about My data?60-250 messages
300Kb Daily average size0.521 Kb/s average rate
30-50 Articles50Kb Daily average size0.521 Kb/s average rate
N/A0.521 Kb/s average rate
20-60 minutes744Kb Daily average size
0.521 Kb/s average rate
10-30 min
372Kb Daily a0.521 Kb/s av
3 - 8 c3350Kb0.521 Kb
10 text me10Kb Daily av0.521 Kb/s av
Daily
5 Hours4826 kb
0.268 Kb/s
It takes me 144,000 hours or 16.42 years of m
to just keep up with the data that Im consum
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What do I do with all of this data
{
People Place Time
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OUr Data versus All Data
All Data = 1,887,438,800,000 Gigabytes
Digital Text Created = 877,189,636.24 Gigabytes
My Data = 1.68 Gigabytes
If your data equals approximately 2 s
All data would equal almost22 million days or just over 59,000
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A change must come
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80%
Automated Understanding: its about the
Awareness
Reading
Relating
Comprehending
Inference
Interpreta
Prediction
Creation
80%
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How do you automate understanding
Inputs
Integrated
Functions OutpUnstructured
Structured
Social
Multiple Languages
Doc SummarizationAssociative NetCo-Reference
DisambiguationLink AnalysisGeo ReasoningTemporal ReasoningFact Extraction
NLP
People undespace and tim
Connectionsand their con
Data fusion sources & typ
Links back tdocument if n
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Deep Dive on automateD understandi
Content IngestMetadata Indexing80%AwarenessReading
Relating
Comprehending
80%
NLP(NER)Doc Summariz
Fact ExtractionGeo Reasoning
Temporal ReasoningLink Analysis
Associative NeCo-ReferenceDisambiguatio
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Synthesys Enterprise Synthesys
Synthesys UI/Gadgets
Business Partners
Application Developers
New Market SolutionsREST API REST API
Unstru
Structu
Social
Multip
How do YOu SCALE AutomateD Underst
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Two Proof Cases(That we can talk about and show in public
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Understanding alice what we bu
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Understanding alice: what we bu
Prediction
Peruna
Training
Analyst
Models
Pierogi Synthesys
Predicted Data
Gold-standard
Human Annotation
Request
models
for livedeployment
Every tagging round creates bettermodel
Creates better predictions
Speeds up tagging
Focuses effort on key classes of error
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Making Sense of Patents Big Data BIGGER D
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Diverse domain of knowledge - alltypes of patents from electrical andprocess to biomedical andmechanical.
Analyzed the full text and claims allpatents after 1976:
10,945,560 patents.
424,698 assignees
2,522,474 Inventors
Making Sense of Patents: Big Data, BIGGER D
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Integrated key structured data into system(inventors, assignees, companies, etc.)
Created and trained categories forextracting domain terms with no rules -only tagging feedback and example words(lexicons).
Making Sense of Patents: The case for Entity Orsimilarity ofEvery PatentEvery Word
Every EntityEvery InventorEvery Company
Every Technology(since 1976)
Just the Beginning
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Just the Beginninghttps://www.synthesyscloud.com/
a change is here now
https://www.synthesyscloud.com/https://www.synthesyscloud.com/ -
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Automated Understanding is the next wave of
Analytics. It deals with your data (vs. your madata) andhowyou makedecisions.
Its here now, but weve only scratched the sur
the value it can create
It gives us hope to reclaim our lives from the aattention and the constant worry of uncertaint
a change is here now
a change is here now
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Understandingempowers
Understandingsecures
Understancreates H
a change is here now
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Questions?
www.digital
http://www.digitalreasoning.com/http://www.digitalreasoning.com/