Gurungo: Coupling Personal Computers and Mobile Devices Through Mobile Data Types

Ivan GonzalezMicrosoft

Jason HongCarnegie Mellon University

1 – Theoretically, Incredible Access

1 – In Practice, Harder to Get Info

• Smaller screens• Slower text input• Slower network speeds

2 – Why Do We Print Maps?

2 – Why So Difficult to Get to Mobile?

• Synchronization tools useful for email, calendar, but still lots of useful information just thru browsing

3 – Re-finding Information is Common

• Tauscher and Greenberg 1997 found 58% of web activity was re-visiting old web pages

• Cockburn and McKenzie 2001 found that 81% of web pages were previously seen

• Obendorf et al 2007 found:– 72% of revisits happen within an hour

– 12% of revisits happen within a day

4 – Not All Information is Equal

• Sohn et al’s CHI 2008 diary study on Mobile Information Needs

• Lots of kinds of information useful when mobile– Trivia

– Directions

– Points of Interest

– Movie times

– Phone numbers

– Flight info

• In many cases, these kinds of mobile data typescan be automatically detected

Gurungo

• Make it easy to acquire and share data you already interact with on PC with mobile device

• Automatic Sharing– Implicitly monitor stream of web pages on PC

– Detect mobile data types

– Annotate the data (e.g. synthesized voice directions)

– Copy data to mobile device

• Manual Sharing– Copy and paste metaphor

Related Work

• Komninos and Dunlop 2007, pre-cache content based on calendar entries– Ex. name of atypical place in calendar, get maps

• Harding et al 2009, plan ahead and show manually entered information based on contextual triggers– Ex. Show travel info based on time

• With Gurungo, cache data that people directly interact with on PC, based on mobile data types– Variant of old idea of locality

Gurungo Overview

• Automatic– Implicitly monitor the stream of web pages

– Detect mobile data types

– Annotate the data (e.g. synthesized voice directions)

– Copy data to mobile device

• Manual– Copy and paste metaphor

• Two data types implemented– Driving directions

– Product details for price comparisons

Detecting Mobile Data Types

• Use a FireFox addon to monitor web pages– Goes thru the HTML DOM

– For predefined web pages, use XPath to get data

– For unknown web pages, use regular expressions and keywords

• We used a hybrid approach– XPath good for hard to specify data (maps, movie times)

– Regex and keywords good for broad coverage

Annotate Data

• Use web services or local programs to improve usability and/or utility of the data

• Driving Directions– Generate synthesized speech

• Product details– Get product reviews

– Get prices on web sites

Copy Data from PC to Mobile

• Proactively copy the data over to the mobile device– Currently, just keeps all info, no garbage collection

Manual Copy and Paste

Mobile User Interface – Directions

Mobile User Interface – Products

Discussion

• Static versus dynamic mobile data types– Driving directions and product details good for months

– Flight information good for … minutes?

– Traffic reports, social events, movie times, store locations

• User interface– Needs to be able to scale up more

– Possible to use location and recency to filter

• Garbage collection– Some data has natural expiration (social events)

– Other data does not, may opt to collect oldest and unused

• Lots of assumptions, need to verify with user studies– Re-finding info on mobile, recency of info

Summary

• Gurungo, a system for coupling PCs and mobiles based on data that people see and use on desktops– Not all data equally useful when mobile, bias UI

– Detects mobile data types based on what people already do

– Annotates data for usability/utility

– Make it easily available on mobile

Gurungo: Coupling Personal Computers and Mobile Devices Through Mobile Data Types

Ivan GonzalezMicrosoft

Jason HongCarnegie Mellon University