Automating Understanding Strata Spring 2012 Final

8/2/2019 Automating Understanding Strata Spring 2012 Final

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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/


20/22

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




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Understandingempowers

Understandingsecures

Understancreates H



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Questions?

www.digital
http://www.digitalreasoning.com/http://www.digitalreasoning.com/

Documents

Automating Understanding Strata Spring 2012 Final