H2O World - Self Guiding Applications with Venkatesh Yadav

© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.

Self Guiding ApplicationsVenkatesh Yadav


Why ?

If an app takes more than a few seconds to learn, a majority of users are going to

uninstall (MOBILE).

Creating that engaging initial use experience is challenging, predominantly

constrained by

Complexity of the app

Screen space

Etc.,

2


Why ?

We want to provide best “Engagement Experience” possible using crowd sourced

application usage data.

3


Self Guiding Applications

4

© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. 5

Self Guiding Applications95

%

Action 1

92

%

Action 2

88

%

Action 3

85

%

Action 4

80

%

Action 5


Phase 1 – Proof Of Concept

6

The Setting

A mobile photo editing app.

Relatively less complicated – approx. 20 possible actions

Constrained in space – ribbon scroll and searching for actions

The Goal

Create engaging user experience, minimize scrolling and searching

Predictive Feature Panel and Contextual Window


Crowdsourced Product Usage Data

7

Each row is a set of actions (like a workflow) performed in an image editing session

Total 100K rows of data, of approx. 20 possible actions

001 002 003


Machine Learning Algorithms

8

Markov Model

Next action is dependent only on the present action, not on the sequence of previous actions

N Action Bayesian Model

Next action is dependent on the sequence of past N actions

N Action Neural Network Model

Next action is dependent on the sequence of past N actions


Performance

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Predictive APIs

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Evaluated few approaches to expose predictive models via HTTP REST APIs

Loose coupling between model creation and consumption

Continuous model development and deployment capability

Create Java POJO for the predictive

model

Wrap POJO by any Java Web API

framework

Can better integrate with Adobe.io

platform


REST API – H2O

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Training

Dataset

Platfor

m

Server

Train Model

Data Science

Team

Smart Apps

Predictiv

e Model

(Java)

Predictive

API (Jar

file)


Demo

“Once models are deployed to the platform, they can

begin receiving API requests and sending predictions back

to the applications.”

Loose coupling

Continues model development

Provide REST API interface to predictive model

(Demo)

Integration into an application (Next Step)

© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential. 13

Demo

Software

H2O World - Self Guiding Applications with Venkatesh Yadav