KM SHOWCASE 2019 - Using Structure in Knowledge Organization

www.synaptica.com - Company Confidential
Using Structure in Knowledge
Organization
Thursday, 4 April 2019
Ahren E. Lehnert, Senior Manager, Text Analytics Solutions
Synaptica, LLC

Born
1973
Became a taxonomist
2002
Talking to you
2019
Ahren E. Lehnert
Senior Manager, Text Analytics Solutions
Information management professional with over fifteen years’
experience in taxonomy, text analytics, search, and content and
records management. Has developed enterprise taxonomies in a
consulting capacity for clients in a broad range of industries.
Likes Dislikes
About Me
@ahrenlehnert
ahren.lehnert@synaptica.com
www.synaptica.com
About Us
Producing enterprise software solutions since 1995 that build and
manage taxonomies, ontologies, and crosswalks; design and deploy
knowledge organization systems; annotate, index and enrich content;
and optimize search, navigation and discovery.
Synaptica, LLC
Contact

The Rhizome (botany)
“In botany and dendrology, a rhizome is a modified
subterranean plant stem that sends out roots and
shoots from its nodes.”*
*"Rhizome.” Wikipedia, Wikimedia Foundation, Inc., 30 January 2019, https://en.wikipedia.org/wiki/Rhizome.
KM

*”Bamboo Removal.” Pullup Stumps, Pullup Stumps, 12 February 2019, https://www.pullupstumps.com.au/bamboo-removal/.
KM

“Deleuze and Guattari use the terms ‘rhizome’ and
‘rhizomatic’ to describe theory and research that allows
for multiple, non-hierarchical entry and exit points in
data representation and interpretation. In A Thousand
Plateaus, they oppose it to an arborescent (hierarchic,
tree-like) conception of knowledge, which works with
dualist categories and binary choices. A rhizome works
with planar and trans-species connections, while an
arborescent model works with vertical and linear
connections.”*
The Rhizome (philosophy)
*"Rhizome (philosophy).” Wikipedia, Wikimedia Foundation, Inc., 21 January 2019, https://en.wikipedia.org/wiki/Rhizome_(philosophy).
KM

Invasive (?)
Non-Invasive (?)
Evolving
Established
Knowledge
Visible
Invisible
Approved
Unapproved
Known
Unknown
Pernicious (?)
Benign (?)
Explicit
Tacit
Factual (?)
Fictional (?)
KM
Structured
Unstructured

KM
CMS DAM Intranet
Process
Process
Process
Processes
Taxonomy
Taxonomy Taxonomy Taxonomy
Taxonomy
Taxonomies Search Email Analytics
Laptops
Process
Process
Process
Workarounds Knowledge Rumors
Information
tombs
External
sources
Scheme
1
Scheme
2
Scheme
3
Competing
structures
Guesses
?
Corporate Structures

Knowledge is abstract
KM

Represent and structure knowledge
visually
KM

Structure knowledge in writing
KM

Written knowledge is unstructured (?)
KM

Structure the concepts in written
language to manage knowledge
KM

• Knowledge management is an attempt to
manage something inherently abstract
• We can add structure to unstructured
knowledge, especially text
• Text is rich, so we lose context and
meaning in the process
Structuring Knowledge
KM

Saturn
Saturn (automobile, defunct)
Saturn (planet)
Saturn (Roman
god, extra creepy)
Saturn (astrology)
Saturn (watercraft, obscure)
Saturn 5 launch vehicles

How can we use various structural levels
in order to add semantic meaning?
In a mixed-domain environment, how do
we disambiguate the same or similar
concepts?
KM

Saturn’s Orbit
The debris field of
language surrounding
our concepts of
interest provide
syntactic and semantic
evidence
The terms appearing
around the term
Saturn provide
evidence telling us
which Saturn it is
Look at the objects
orbiting the concept
Use existing structures
and impose artificial
structures
KM

From Chaos to KOS
+
+
A knowledge organization system (KOS) of taxonomies and ontologies
Document structure inherent in rendering text for visualization
Natural Language Processing (NLP) and text analytics

KOS

KOS
• Taxonomies are the “arborescent (hierarchic, tree-like) conception of knowledge”
which work with “vertical and linear connections”
• “The tree or root, which plots a point, fixes an order.”*
• Taxonomies are artificial constructs organizing terms and concepts
• Taxonomies represent the organized viewpoint of the business
• Ontologies are the “non-hierarchical entry and exit points in data representation
and interpretation” which work with “planar and trans-species connections”
• “Principles of connection and heterogeneity: any point of a rhizome can be
connected to anything other, and must be.”*
• Ontologies are artificial constructs organizing terms and concepts
• Ontologies represent the organized viewpoint of the business integrated with the
external world
*Deleuze, Gilles, and Felix Guattari. A Thousand Plateaus. Minneapolis: University of Minnesota Press, 1987.

Saturn (planet), hierarchy, and
related terms
Taxonomy Structure
Term placement in the hierarchy and relationships to other terms provides structure and context
KOS
Saturn (planet) #fakeplanet
#plutoplanet

Structural Levels: Taxonomy
• Terms are selected, curated, and
normalized as common, preferred forms
• Term placement in the taxonomy
determines their role in text
Preferred Term Preferred Term SiblingRelated Term …
KOS

Taxonomy & Rules Structure
The term, its parents, and related terms use taxonomy structure to create classification rules
KOS

Structural Levels: Language
• Even “unstructured” text has structure as
defined by the rules of the language
• Linguistics and the subfields of
morphology, syntax, and semantics are
the basis for text analytics
Noun Verb Adjective Noun …
NLP

Language Structure
Language offers structure adhering to linguistic rules
S V O
Nouns
Pronouns
Direct Objects
Indirect
Objects
Transitive
Verbs
Intransitive
Verbs
Adjectives Adverbs
Prepositions Conjunctions
Determiners
Interjections
NLP

Structural Levels: Document
• Text structured for electronic rendering
• The various components of the document,
in markup or as rendered on the screen,
provide structure
Header Paragraph
Table of Contents
Link …
Wikipedia Article
DOCS

Document Markup
The document markup provides structure
DOCS

Document Text
The rendered document text provides structure
DOCS

DOCS

Unformatted Text
The raw text document provides little structure
DOCS

Document Section Structure
Use the markup of the text to create document sections
DOCS

Document Section Structure
Use the text as rendered to create document sections
DOCS

DOCS
From Chaos to KOS
KOS NLP
Preferred Term
NLP
Related Term

DOCS
Do Not Annotate
KOS NLP

• Use a knowledge organization system of
taxonomies and ontologies to create a
semantic layer
• Text analytics and natural language
processing use the inherent rules of a
language and writing structures to define
meaning
• Document encoding and presentation
provides existing structures we can use in
conjunction with taxonomies and linguistic
analysis
In Summary

Surface unstructured knowledge
KM

@ahrenlehnert
ahren.lehnert@synaptica.com
www.synaptica.com
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KM SHOWCASE 2019 - Using Structure in Knowledge Organization

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