1. Stacy Faught
IT Business Solutions
11/18/2016

2. Introduction
GOAL OF THIS PRESENTATION:
Define text analytics capabilities to
build the business case for
creating the service.
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creating the service.

3. Ontology Of Text Analytics BUZZ Words
Text Analytics
Text Mining Big Data
Linguistics
Machine
NLP
associated withassociated with
relies upon
sub-discipline of
works
together
with
technology
tools for
works
together
with
Faceted
Search
enables
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Taxonomy
SyntaxSemantics
Machine
Learning
OntologyThesaurus
Semantic Network
Synonymous
with
with
more
complex
more
complex
used to
build
Morphology
Disambiguation
Entity Extraction
Sentiment

4. Beginnings
Text analytics leverages
and learns from massive
quantities of textual
data to reveal customer
intentions and
sentiment…
Text Analytics World
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Text Analytics World

5. Gaining Interest
Text Analytics is the
process of deriving
information from text
sources.
Gartner
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Gartner
Text Analytics is a
method for making
unstructured content
useful and accessible.
Expert System

6. It’s All About the CONCEPT
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7. CurrentState - Keyword Searching
All these documents contain the
keywords “big cat oil discoveries”.
Read ALL the documents to find the
ones relevant to you.
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8. Keyword Search Not Always Enough
Advantages
 Speculative searching (i.e. Where are the best tacos in Houston?)
 Finding general information (i.e. Address of Access Sciences’ website)
Disadvantages
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 Large result sets mean not enough time to read all documents
 Noisy and irrelevant hits have to be filtered out
 Narrowing the question may mean missing a key result
 Have to type in all variants of a term
 i.e. significant oil discovery, large oil find, >200M barrels???

9. What Text Analytics Does
TYPICAL SEARCH
Text Analytics occurs here
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INDEX
Text Analytics occurs here
Analyzes content & extracts meaningful metadata
Entities
Themes
Sentiment
SMARTER Searching

10. How it works
Concept:
big cat
Definition:
Carnivorous
mammal
Child:
Jaguar
Relationship:
Wild
Synonym:
Constraint:
Not domestic
Parent:
Mammal
Concept:
big cat
Definition:
Caterpillar
machinery
Child:
Drilling
equipment
Relationship:
Mining
Synonym:
Heavy
Constraint:
Not Hitachi
Parent:
Equipment
Definition:
Large oil
discovery
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Synonym:
Feline
Heavy
equipment
Concept:
big cat
discovery
Child:
Shale big cat
Relationship:
Elephant
Synonym:
Significant
Constraint:
>200Mboe
Parent:
Oil discovery

11. Interpretingthe meaning of text
• Groups words into meaningful units
• Searches for different forms of words (morphology)
• Searches for words with semantic relationships
sentences Noun groups
Match entities
verb groups
Match actions
morphology
Match different forms
semantics
Match related meanings
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Match related meanings
Total has confirmed just one “big cat” -- with more than 200 million barrels -- in
Bolivia in May 2011 that extends a 2004 discovery.
Shell has discovered oil on three big cat prospects offshore Nigeria, plus a large gas-
condensate field in the Norwegian Sea.
Firm makes major Gatwick oil find.

12. Automatically Extract Known Entities
People OrganizationsPlaces
Total S.A.
Europe
France
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• Entity extraction
Total S.A.
– French oil & gas co.
vs.
total - adj. meaning entire
Saudi Aramco
Royal Dutch Shell
Exxon Mobil
Erle P. Halliburton
Charles Holiday
– Shell Chairman
vs.
4th of July Holiday
France
Paris
Monaco
Tyrrhenian Sea
Oceania
Basins
Plays
Fields

13. Put the Puzzle Pieces Together…
Concepts:
 Big Cat
 Discoveries
 Prospects
 Play
Entities:
 Organizations
 Shell
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• Faceted search
 Play
 Shale
 Conventional
 Shell
 Total
 Places
 Africa
 S. America

14. Find the Missing Piece
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15. Automatically Extract Relevant Facts
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WHO WHEN WHERE
Total May 2011 Bolivia
Shell July 2005 Offshore Nigeria
UK Oil and Gas April 2015 Sussex

16. Use Cases
 Auto Classification
 Competitive Intel
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17. Auto Classification
Internal Data Sources
 In Place
 Share Drives
 Legacy Datasets
 Migrations
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• In its simplest form
 Migrations
 Consolidation/Expansion
 Mergers and Acquisitions

18. Competitive Intel
External Data Sources
 Public Domain
 Industry Publications
 Regulatory Reporting
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19. Industries and Drivers
 Oil & Gas
 Pharmaceuticals
 Government Agencies
 Legal
Competitive Intel
Research
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20. Knowledge Areas/Roles
 Text Mining
 Library Sciences
 Taxonomy
 Linguistics
 Foreign Language
 Technology
 Domain Expert
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 Domain Expert

21. Technology Tools
 Expert System Cogito
 conceptSearching
 Smartlogic Semaphore
 HP Autonomy  Linguamatics I2E
 SAS Text Analytics Suite
 IBM Languageware / Content Analytics
 Lexalytics Text Analytics
 Provalis Research QDAMinder / WordStat
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 Provalis Research QDAMinder / WordStat
 PingarAPI
 AlchemyAPI
 Content Analyst
 Angoss KnowledgeREADER
 NetOwl
 Language Computer Corp.
 Basis Technology
 MeaningCloud
 Forest RIM’s Textual ETL

22. Q & A
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