Semantic Solutions from Information Exploration.pptx

The Daedalus A predictive search suggestion and exploration engine.

Information Exploration, LLC

EI

© 2013 Information Exploration, LLC

Welcome

Google estimates that 99% of all searches are answered on their first

page, but at 2 million queries “per

minute” that leaves 2,880,000,000

unsatisfied customers every day!


Welcome

“Daedalus is predictive search

visualization.”

“Daedalus is a user driven

solution to Big Data.”

“Daedalus lets you discover what

you are looking for, on the web, at a store and in the lab.”


Outline

OUTLINE


Our Team

• Sean Connolly – Human Computer Interaction – Bachelor’s Degrees from Duke University in Psychology and English.

– In 2000, he sold the start-up Scriptshark.com with movie producers Roy Lee and Ed Kashiba (The

Departed, G-Force).

– Currently holds a MS/MA in Human-Computer-Interaction-Design and Telecommunications and

researches and produces American 3D movies. He combines visual language with 3D interactions in the

Daedalus.

• Brent Kievit-Kylar – Natural Language Processing – Bachelor’s Degree in Computing from Queens University.

– Currently researches Natural Language Processing as a PHD candidate in Mike Jones’s computational

cognition lab.

– His recent work in information visualization led to a publication in Behavior Research Methods (2012)

and the Castellan Award in the field of computational psychology for visualizing word similarities.

• Rick Connolly – Strategic Advisor – Bachelor’s Degree Business and Finance from Wake Forest University

– He was Vice president Sales and Operations of a private company with 10,000+ employees and

eventually President of a spin off from parent company.

– Currently, SVP Strategic Sales and Marketing at a publicly traded 600,000+ employee global

organization.


The Problem

• Search algorithms have been improving; yet, the interface has remained largely the same

1998 2013


The Problem

• The problem is not with the retrieval algorithms, but

with the polysemous nature of natural languages1

• Humans only generate the same words to describe common objects 20% of the time

– This extends to search queries as well (Fidel, 1985)

1Furnas, Landauer, Gomez, and Dumais (1987)


The Problem

McRae K et al (2005)


The Problem

The successful candidate will have an excellent academic record with demonstrated laboratory skills and the ability to work in an

interdisciplinary team environment. Experience in chromatography and wet analytical chemistry is desirable. The candidate for this position should have a B.S. or M.S. or PhD

degree in Chemistry with at least 5 years of relevant experience.

Develops and validates analytical methods (HPLC and GC) for raw materials, intermediates and drug substances.

Writes standard operating procedures (SOPs) and qualification protocols for equipment, instrumentation and

operations in cGMP processes.


The Problem

(“PhD” OR “Ph.D.” OR “Dr.” OR “Doctor”) OR (Master* OR “M.S.” OR “MS”) OR

(Bachelor’s OR “B.S.” OR “BS”)


The Problem

The successful candidate will have an excellent academic record with demonstrated laboratory skills and the ability to work in an

interdisciplinary team environment. Experience in chromatography and wet analytical chemistry is desirable. The candidate for this position should have a B.S. or M.S. or PhD

degree in Chemistry with at least 5 years of relevant experience.

Develops and validates analytical methods (HPLC and GC) for raw materials, intermediates and drug substances.

Writes standard operating procedures (SOPs) and qualification protocols for equipment, instrumentation and

operations in cGMP processes.


The Problem

chem* AND ((((“PhD” OR “Ph.D.” OR “Dr.” OR “Doctor”) OR (Master* OR “M.S.” OR “MS”) OR

(Bachelor’s OR “B.S.” OR “BS”) AND (“HPLC” OR “H.P.L.C.” OR “High-Performance Liquid

Chromatography” OR “High-Pressure Liquid Chromatography” OR “High Pressure Liquid-

Chromatography” OR “High-Performance-Liquid Chromatography” OR ““High-Pressure Liquid-

Chromatography” ) AND (“Gas Chromatography” OR “Gas-Chromatography” OR “GC” OR “G.C.”)) AND

(cGMP OR GMP OR “G.M.P.” OR “c.G.M.P.” OR “Good Manufacturing Practices” OR “Good Manufacturing

Protocols” OR “current Good Manufacturing Practices” OR “current Good Manufacturing Protocols”)))


Introduction to Solution

• The solution is not more Boolean logic

• It is letting the user speak more directly with the algorithm

• It is putting the people back into the search


What it Works With

The domain space

– Meta objects - Things

– Domains - Properties

– Features - Values


How it Works

Interactive exploration loop • Human thinks

• Computer predicts


How it Works

Visualization

– Window for each domain and for meta objects

– Values appear as bubbles in the windows

– Color indicates human or computer values


How it Works

Semantics of the search space

– Position is key

• Close to center – more relevant

• Close to each other – more similar


Mobile Technology

• Reduce Typing

– Words are suggested and may be

selected without having to type

• Natural Interface

– Sliding nodes on a surface is more

intuitive with touch

DAEDALUS

DAEDALUS


Telling a Story

Insert video of prototype here


Testimonials

• Domain expert testing

– Philosophy PhD students that we did not know asked to use the

system.

• No information on what it is or how it worked

• Able to use the tool very quickly

• Described stories about why specific words that they had not expected

(but had shown up) should be there

• Interesting remarks

– “I think you’re undervaluing this.” Ken Green – Innovate Indiana

– “This is so easy, I feel like I’ve used this before” – multiple beta testers


Market/Value

• Consumer – Web Search

• Google ($192 billion)

• Other Web Search ($48 billion)

– E-commerce • Amazon ($100 billion)

• eBay ($61 billion)

– Job sites • CareerBuilder ($2 billion) • LinkedIn ($9 billion)

• $ trillion market • 1% of 1% is $50 million

• Industrial – Big Data technology and

services will become a

$16.9 billion dollar

industry by 20151

• Fluid market that is

growing rapidly


Monetization

• B2B License – Attempt to develop corporate partners

– Learn and build on each iteration with larger companies

– Flat fee or usage based

• Commission – Make revenue through commissioned links

– Facilitates people finding products

– Take percentage of purchase


Competition


Budget

Perfect Two Client Platforms: $60,000.00 Integration Specialist $12,000 (3 weeks at 100/hr) Graphic Designer $12,000 (3 weeks at 100/hr) Brent & Sean $2,000 (5 day at location stays) Network Specialist $4,000 (1 week at 100/hr) Sub-total 1 Trip $30,000

Platform Specialists: $8,0000

iPad specialist $4,000 (1 week 100/hr) iPhone specialist $4,000 (1 week 100/hr)

Additional Legal: $5,000

Technology and Licenses: $2,000 iPad, Android, iPhone $1,500 iPad, Android, IPhone licenses $500

Time and effort Principles: $15,000 Sean $5,000 Brent $5,000 Rick $5,000

Marketing and Sales: $8,0000

Total: $100,000

Perfect One Client Platforms: $30,000.00

Integration Specialist $12,000

Graphic Designer $12,000

Brent & Sean $2,000

Network Specialist $4,000

Additional Legal: $3,000

Time and effort Principles: $12,000

Sean $4,000

Brent $4,000

Rick $4,000

Marketing and Sales: $5,0000

Total: $50,000


Timeline

• Milestones: – First web prototype January 2012

– Lawyer interviews March 2012

– First Big Data Prototype May 2012

– Provisional Patent August 2012

– First beta-tests (with local academics) November 2012

– First tests (business intelligence) May-July 2013

– Full patent June 2013

– Wide release / license / sales October 2013


Thank you

Thank you! Questions?


Backup Slides


The Problem

• Thesauri and deep semantic indexing help but still remain a source of error

• Lack of visualization prevents comprehension of the search space

• Searchers who can’t refine their queries often abandon search (Pirolli, 2007)


The Solution

Guiding principles

– Consistency – Confidence

– Feedback – Exploration

– Interactivity – Insight

Early Iterations

Learning Through

Visual Interaction


Papers

Related papers we have authored:

• Connolly S. (2012) Artifacts on the horizon

• Kievit-Kylar B., Jones M (2012) Visualizing multiple word similarity measures

• Bailey R., Connolly S., Lang A (2013) Pictures enable action, words enable thinking

• Kievit-Kylar B., Connolly S., Allen C., Jones M (in review) Exploiting Semantic Associations to Improve Search on the Web


Google Problems

• Examples of difficult Google searches – Value of the company Mathematica

– Chi visualization

– Tip of the tongue – what is that word? The thing that does the thing?

– A Google a Day • http://agoogleaday.com/

• Game created by Google that proposes hard questions to solve

• Can be solved with Google, but difficult


Provisional Patent

•Why we got the provisional patent • Can’t get a full patent? No.

• It protects us from the big players

• We can keep our idea secret from other companies

while we get started


Extra Materials


[email protected] 1-310-801-7642

“Daedalus is a user

driven solution to Big Data.”

“Daedalus is predictive

search visualization.”

“Daedalus lets you

discover what you are looking for, on the web, at

a store and in the lab.”

Handout

Front

Google estimates that 99% of all

searches are answered on their first page,

but at 2 million queries “per minute”

that leaves 2,880,000,000

unsatisfied customers every day!

This is our untapped market.

Handout

Back

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Semantic Solutions from Information Exploration.pptx

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Transcript of Semantic Solutions from Information Exploration.pptx