Semantic Clustering for Nomenclature Purposes

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Semantic Clustering for Nomenclature Purposes by Sean Howard
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    21-Oct-2014
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    Technology

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A bit of an idea on how to better capture meaning and semantic relationships within domains. Digitally slanted but could be applied from everything from a nomenclature task to engagement strategies.

Transcript of Semantic Clustering for Nomenclature Purposes

Page 1: Semantic Clustering for Nomenclature Purposes

Semantic Clustering for Nomenclature Purposesby Sean Howard

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A very smart man

Matthew Milan: http://tinyurl.com/3nklu8

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A very smart man

recently said,

“It's time to seriously invest in a new set of tools, and we're going to need to build

some of them from scratch.”

“In the last five years, I can't identify a single original method that has grown up

inside the IA field.”

Matthew Milan: http://tinyurl.com/3nklu8

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which got me thinking

about MEANING and how we struggle

with defining RELATIONSHIPS

that bring VALUE to a domain

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or more specifically

NOMENCLATURE

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Every UX job generally involves a nomenclature review, refinement or overhaul at some point or another

How do we come up with our final recommendations?

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I know a firm that hires a third party semiotician to define the value and meaning relationships for a project

A black box solution, if you will

Image Source: Mr. Noded, http://flickr.com/photos/jrnoded/

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The rest of us tend to use

card sortbrainstorm thesaurus

content audit

theft etc.

Image Source: Jacob Bøtter, http://www.flickr.com/photos/jakecaptive/

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not to mention a stiff drink

(or three)

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and then we test, refine and repeat

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What if there was a better way

to identify semantic relationships with

our actual audience?

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What if there was a better way

to identify semantic relationships with

our actual audience?

more MEANINGFULnomenclature

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What if we could build a map of meaning

For more information:

Semantic Memory: http://en.wikipedia.org/wiki/Semantic_memory

Priming: http://en.wikipedia.org/wiki/Priming_(psychology)

and explore proximity by association

to better understand our audiences?

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I give you: a semantic mapping tool

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Here we see sample results in aggregate showing potential meaningful relationships held in common for one term

This could be further segmented by a number of other factors (demographic, psychographic, etc.)

Term: Consumer

Pro

duc

t

Per

son

Mar

ketin

g

Goo

ds

Falla

cy82

6858

4234

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Not everyone types at the same speed. Let’s define the avg. time to enter a word* from first keypress to last keypress as tkey

tkey is 1.34 seconds

* A word being defined by the act of the user pressing the submit button.

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tthink can then be total time minus tkey where tthink can then be used to define those words that come quickest/easiest

tkey

total time from presentation of word to submission of word by the user

Note: deleting of the letters and starting over likely needs to be taken into account as well

tthink

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We may want to segment clusters based on a factor of tthink (those that came to your audience quickest.)

Term: Consumer

Pro

duc

t

Per

son

Mar

ketin

g

Goo

ds

Falla

cy

< 1.25 sec

< 2.50 sec

> 2.50 sec

82

6858

4234

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Or alternatively, show words as nodes in a network diagram where the length of the line is the average speed to come up with the word.

There may also be value in the order in which words are entered.

Product

Person

Goods

Fallacy

Marketing

Term: Consumer

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This is about building a better understanding

of the language and meanings pertinent

to the stakeholders within a domain

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I ran a simplified version of this experiment with three friends

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Financials

bankaccount

money

hat

market

suit

I ran a simplified version of this experiment with three friends

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company

measurements

pale green

CFO

charts

projections

spreadsheets

Financials

I ran a simplified version of this experiment with three friends

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corporate

investing

results

brownies

annual reports

Financials

I ran a simplified version of this experiment with three friends

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Two of my subjects show signs of a more personal relationship with “financials”

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One appears to relate stronger to financial presentations

Two of my subjects show signs of a more personal relationship with “financials”

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The terms “hat”, “pale green” and “brownies” are some of the areas I would be curious to explore further

Two of my subjects show signs of a more personal relationship with “financials”

One appears to relate stronger to financial presentations

Ann did mention being hungry during the experiment.

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greater

INSIGHT

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better connect with our audience

Enabling us to create better content,

define stronger navigation, and

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Anyone want to build this? Go for it.

This work is licensed under the Creative Commons Attribution 2.5 Canada License. To view a copy of this license, visit http://creativecommons.org/licenses/by/2.5/ca/

Questions or Comments?

Find me at: http://www.craphammer.ca/