Ajax Prediction

Uzanto Consulting IA Summit 05

Making Magic Happen: Predicting User Behavior in AJAX applications

Jonathan Boutelle

Uzanto Consulting


Who am I?

• www.uzanto.com

• www.jonathanboutelle.com




HTML Server

Http request

Initial Html

User action

Html (with data embedded)

Dbase

Vanilla Web App (circa 2000)

User action


…


HTML

Http request

Initial Html

User action


Vanilla Web App (circa 2000)

User action


…

Server Dbase


Rich Internet App (circa 2003)

Http request for app

App (lActionScript and Flash) downloads

User action that requires data Data

UIClient

Manager Server Dbase


Rich Internet App (circa 2004)


App (Flash and ActionScript) downloads

User action that requires data

Optionally preload data

UIClient



Ajax Application (circa 2005)


App (HTML + Javascript) downloads

User action that requires data

Always preload data

UIClient




Building a model of user behavior

• Build naïve model

• Validate and refine model

• Be metric driven Responsiveness: % user data requests that were met

with pre-fetched data Efficiency: the % of pre-fetched data that ended up being

used



Preload Cost

the extra cost assumed by preloading:

{cost of download} *

(1-{odds data will be requested})


Preload Value

value of reduced latency *

odds the data will be requested


Download if value > cost

• Value = value of reduced latency * odds the data will be needed

• Cost = cost of download * odds the data won’t be needed

Uzanto Consulting IA Summit 05Odds the data wll be used 100%0%

value

cost

Value vs. Cost


Odds the data wll be used100%0%

value

cost

Increasing Value of Preload


Odds the data wll be used100%0%

value

cost

Decreasing Value of Preload



value

costOdds content will be requested

Importance of low latency

Technology

Ajax Prediction