YOUTUBE Under Armour Innovation Search Project

This is an Innovation project concept searching for specific niche innovation online.

THE PROTOTYPE:
The demo and supporting documentation provided outlines what it takes to find innovative videos pertaining to shoes 
from YouTube in Near real-time (NRT).
See main algorithm, query-shoe.conf

The prototype is designed and built by me (Ian Robertson), and provides a specific detailed analysis of all shoe(s) videos 
on the Google YouTube API.

I use scoring as a means of determining statistically whether a newly-uploaded video contains the relevant content (i.e. words)
that are directly associated with innovation.

To do this, I must consider four components of any form of innovation:

  1. Nomenclature
  2. Anatomy 
  3. Creative Expressions
  4. Uniqueness 
  
The main part of the "algorithm" explores the concept of leveraging Distance-Vector analysis 
using a logarithmic scale base10 of key words and phrases commonly associated with innovation.

A Premise for any Search Framework:

An organization searching for a specific product enhancement or feature (Innovation) should leverage an
iterative algorithmic search for external knowledge that encompasses situated search paths, analogical search paths, 
sophisticated search paths, and scientific search paths.

Once a specific instance is found and deemed relevant to the initial objective, 
I believe that a recursive search pattern should be automated to determine the strength of the iterative search path, 
and whether any adjustments need to be made to the former.
 
The "Algorithm":

*Written in Ruby
*Runs within Logstash, Outputs to Elasticsearch, viewed on Kibana (UI)
*Performs:
Tagging => Preprocessing => parsing => aggregation of terms => by-word parsing then looping => scoring =>
labeling => insert back into Backend.

Located: /etc/logstash/conf.d/query-shoe.conf

Project Highlights;

1. Setup Server
2. Installed/upgraded software
3. Configured applications
4. Created Dashboards & Visualizations
5. Created Email and Dashboard Alerting
6. Developed and ran ingest pipeline
7. Built data storage, and retrieval process

Shoe Innovation Search:

OBJECTIVES:
Find videos that express innovative uses pertaining to shoes.
Identify context, creative expression, innovative components (nomenclature) on various parts of the anatomy.

Creative, Anatomy, Nomenclature (CAN) words/expressions:

Only score CAN words: Creative, Anatomy, Nomenclature
Usage: per each CAN word in C(sub-i) recursively move to last starter word and count distance for Distance Vector.

Identify distance between critical words and directional word flow pattern.

i.e. “My new welt design” or “This new insole technology I designed” 


The Abstract Feed Query:

https://<GoogleAPI>/search?part=snippet&order=date&q=shoe%7Cshoes&relevanceLanguage=en&maxResults=20&fields=items(id,snippet(title,description,channelId,channelTitle,publishedAt,liveBroadcastContent))&type=video&key=<KEY>


Terms Consideration Discussion:

Assess what are Positive and Negative Terms.
Impacts scoring. See, “terms_score” in Kibana.
+1 for positive terms, -1 for negative terms.
Videos w/ score at or below 0 are typically non-conducive. 

Vital Considerations: 
Nomenclature
Anatomy 
Creative Expressions
Uniqueness 
In all probability, a video of a unique innovation will have attributes of all four.

---
Nomenclature (in this case of a shoe):

Laces, arch, outsole, insole, vamp, welt, eyelet, leather, material, quarter, tongue, feather, lining, seat, shank, 
throat, waist, puff, upper, lower

---
Anatomy (of how the user uses a shoe) i.e. End User considerations:

Ankle, arch*, men, women, toes, calf, legs, comfort*, fit, motion, muscles, length, width, health, foot, feet, round, flat, curve

Uniqueness:
 Creativeness Expressions in use/form of Prepositions, individual, and possessive terms:
  For, my, mine, I, I am, I’m, you’re, your, man, woman

---
Creative Expressions:
  Design, designed, pattern, patent, tech, technology, latest, innovation, idea, create, creation, created, running, 
  develop, developed, tested, test

---

What are the components and functions of a shoe?

  words = ['laces', 'ankle','arch','foot','feet','wear','design','designed','heel','tested','test',
  'outsole','sole','puff','shank','waist','upper','lower','throat','seat','tongue','feather', 
  'lining','mens','womans','going','completed','muscles','muscle','motion','length','width',
  'health','fitness','vamp','welt','insole','eyelet','toe','toes','leather','material','calf',
  'leg','pattern','quarter','patent','man','men','woman','women','resist','resistant', 'weather',
  'develop','developed','built','comfort','stability', 'grip', 'lacing', 'round', 'flat', 'curve', 
  'fit', 'tech', 'technology', 'latest', 'lace', 'for', 'running', 'run', 'my', 'new', 'innovation',
  'idea', 'create', 'creation', 'created']

What are the negative words that may negate the relevancy of the specific video in question?

example:
negate_words = [ 'nike', 'brooks', 'collection', 'collect', 'jordan', 'curry','lonzo','lebron',
'durant','lavar','subscribe','reebok', 'adidas', 'northface', 'newbalance', 'review', 'sale',
'offer', 'live','cheap','ebay','discount','amazon', 'buy', 'top', 'best', 'how', 'free'  ]

How negation works:
We must asses the negative categories that are disproportionate to our objective of finding innovative shoe videos:
In theory this can and should be automated, however, automation was not a consideration for 
this algorithm because of financial and time constraints.

OBJECTIVES:
Remove Reviews, How-to’s
Remove Competitors and their references
Remove sales pitches (free, cheap, ebay, amazon, discount)
Negate Athletes (Jordan, Curry, LeBron)
Negate professional channels (subscribe)

---
Additional things to consider for alerting algorithm:

Frequency : 
Uses: Occurrences of any given word
Example: 3 references to Under Armour in Title.

New Term :
Uses: For finding new uses of specified value
Example: Finding New Channels in Fitness data.

Spike: 
Uses: Trending Events 
Example: Increase in references to “shoe”

The Youtube API:

Allows you to gather videos as they are uploaded to YouTube or search existing content.
Filter criteria into topics, keyword, relevance, channels, or users

Initial Project Proposal and Design:

(pull data from a broad range of fashion topics)

-General (All new)
-Lifestyle
-Fashion
-Fitness
-Technology
-Under Armour Channel
Competition (Nike, Reebok, Adidas) Channels
**Topics (General Pipeline Parsing, TBD)

Dashboards in Kibana:

-Home dashboard
-Alerting history
-Visualizations
-Competition
-Innovation
-Live Broadcast

Random Additional considerations for integrating:

*Decay function – The distance between key words
*Propagation – Occurrences, duplicates and synonyms
*Coercion  - synonyms (spread patterns or numerical analysis into metadata)


Innovation precursors:
A silly easy way to keep your running shoes in top condition.
https://www.youtube.com/watch?v=uawNiGjAcgY
Differences Between Hard and Clay Court Tennis Shoes (w/ Bethanie Mattek-Sands)
https://www.youtube.com/watch?v=MyANkWDXUyQ
Ladies Gym Trainers Walking Trainers Womens Fitness Lightweight Sports Running Shoes
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Crayola Shoe Studio Unboxing Create Your Own Designer Shoes | Design your Shoes
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Dr Comfort Diabetic Shoes Men's
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Get inspired - passion and craftmanship for cycling shoes @ Northwave -
“The development of a cycling shoe. Inspired by the needs of the athletes
and realised with a combination of pure craftmanship and high technology.”
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