TrailMap : Facilitating Information Seeking in a Multi-Scale Digital Map via Implicit Bookmarking

TrailMap: Facilitating Information Seeking in a Multi-Scale Digital Map via Implicit Bookmarking

Jian ZhaoDaniel WigdorRavin Balakrishnan

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Travel to Paris: Love or Hate?Explore cultural neighborhoodsTaste local deliciousVisit various places of attractions…

Need a lot of searchingDemand careful planningProcess and compare large amount of informationBrowse unfamiliar geographical regions…

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Dining out in Paris

Search “restaurant” on Yelp

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Revisitations in Multi-Scale Mapso Explicit bookmarking: disadvantages

− Additional cognitive burden− Interrupt the interaction flow− Require users to anticipate the revisitation

o Implicit bookmarking: challenges• Continuous information space• Heterogeneous interactions in a multi-scale 2D

navigation• Dynamic meta-information content

Develop an implicit bookmark generation algorithm and a web app prototype called TrailMap for multi-scale digital map navigation

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Welcome to Toronto: Demo

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User Interaction ModelTime

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User Interaction Model

a b c

a

b

c

Time

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Implicit Bookmark Generation

Searches

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Implicit Bookmark Generation

Long Distance Pans or Zooms

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Implicit Bookmark Generation

Long Time Dwells

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Implicit Bookmark Generation

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Algorithm Diagram

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Evaluationo Participants

• 4 females and 7 males: aged 20-31, from different academic backgrounds

• Use of existing online map applications: 6-10 times/week and 5-10 minutes/session

o Apparatus• Personal desktops/laptops via IE, Chrome, Firefox,

Safari• A Windows IIS server for hosting TrailMap

o Procedure and Design• Pre-study tutorial• One week deployment study • Post-study questionnaires and interviews

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Quantitative Results

Frequency Frequency

Part

icip

ant

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Qualitative Results

1-10 Likert Scale (Strongly-disagree to Strongly-agree)

Question Mean SDQ1. Overall I was satisfied with the design of

this application. 7.9 0.9

Q2. The interface of visiting and manipulating bookmarks was easy to use and intuitive. 8.1 1.4

Q3. The interface of exploring search results (e.g. fading-out labels) on the map was helpful.

8.1 1.2

Q4. The automatically generated bookmarks were helpful in map exploration and search tasks.

8.3 1.3

Q5. The functions of logically revisiting multiple bookmarks were helpful. 8.3 1.3

Q6. I’d like to have a plugin of auto-bookmarking functions with the existing online map applications.

8.9 1.3

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Future Worko Develop smarter bookmark generation

algorithms using machine learning and natural language processing

o Support importing, exporting, and sharing of implicit bookmarks

o Extend to other devices including mobile phones and tablets

TrailMap: Facilitating Information Seeking in a Multi-Scale Digital Map via Implicit Bookmarking

Jian ZhaoDaniel WigdorRavin Balakrishnan

jianzhao@dgp.toronto.eduhttp://www.cs.toronto.edu/~jianzhao

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Space-Scale Diagram

x

y

z

A

B

u

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G. W. Furnas and B. B. Bederson. 1995. Space-scale diagrams: understanding multiscale interfaces. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '95), pp. 234-241.