Adaptive Mobile Guides - University of Pittsburghpeterb/2480-012/AdaptiveMobileGuides.pdf ·...
Transcript of Adaptive Mobile Guides - University of Pittsburghpeterb/2480-012/AdaptiveMobileGuides.pdf ·...
INFSCI 2480���Adaptive Information Systems ���
Adaptive Mobile Guides
Peter Brusilovsky School of Information Sciences University of Pittsburgh, USA
http://www.sis.pitt.edu/~peterb/2480-012/
The Vision
Introduction
Limited Resources
Technical resources
Cognitive resources
Screen size
Bandwidth
Ergonomics
Connectivity
Attention span
Cognitive load
Unfamiliarity
Display resolution
Time pressure
Adaptation on a desktop is a luxury. Adaptation on a mobile device is a necessity. Barry Smyth
User-Adaptive vs. Context-Based
1. Context-based, not adapted to the user as a person 2. User-adaptive but not context-based 3. Context-based and user-adaptive
User-adaptive Context-based
2 3
1
What is the Context? Environment User Task
1. Technical (devices and services in use and available)
2. Physical (place, location coordinates)
3. Ambient (e.g. temperature, noise, lightness)
4. Social (e.g. cultural environment, people near by)
1. Abilities, skills, knowledge, habits, feelings
2. What the user has in mind, where his/her attention is
What the user 1. is doing 2. has been doing 3. plans to do
A prospect of context-based and ubiquitous computing
Four Dimensions for Mobile Guides
User-adaptive
Platform-adaptive Social
Location and context-based
How to Model
• Modeling user/community characteristics – Traditional UM approach – observing user/
community, asking the users • Modeling device characteristics
– Device profiles • Modeling location and context
– Sensing! – Location, acceleration, light, time…
Ontology-based Modeling Mobile applications require a variety of spatial, temporal,
physical, and activity Using Ontology model
o To enable exchange of knowledge o To share common understanding of the structure of
information among people or websites o To enable reuse of domain knowledge o To separate domain knowledge from the operational
knowledge
Users, context and situation modeling: an ontology-based approach
UbisWorld: the modeling and representation of users, context, and situations
An Ontology for Location Modeling
UserML forms the syntactic description in the knowledge exchange process Semantic definition of each concept is defined in GUMO
GPS Where am I?
Cell Tower
Bluetooth
Detecting Location
Outdoor Indoor
City/Navigation Guides Museum Guides
Shopping Assistants
City Guides: Guide o A context-aware tourist guide
o User Interests o Location o Time of the day
• Provide a tailored-tour of the city • Example of adaptation-Nearby
attractions page – system performs both filtering and
information visualization – uses visitors current location,
attractions already visited • Uses two models
– user model (wizard type interface) – environment model (information
regarding attractions within the city)
Cheverst, K., Mitchell, K., and Davies, N. 2002. The role of adaptive hypermedia in a context-aware tourist GUIDE. Community. ACM 45, 5 (May. 2002)
• Network cells defined by strategically placed wireless access points determine current position of the user (does not rely on GPS)
Guide: The Sensing Part
• MoG, the mobile guide, providing multimedia content about the city of Cesena, using both WLAN and GPRS
• MoG devivered multimedia content MoG uses W3 standard SMIL (Synchronized Multimedia Integration language)
MOG (2003)
A Multimedia Mobile City Guide for Outdoor Learning Paola Salomoni (2003)
• A context-aware tourist guide that assists roaming tourists
• Approach used: the deployment of intelligent agents which collectively determine the user context and retrieve and assemble multi-media presentations that are wirelessly transmitted and displayed on a PDA • As tourists near attractions, Genie displays an
electronic map with their position and orientation highlighted on it.
• As they approach a tourist attraction, Genie will start pre-caching a presentation.
• When user is at attraction, attraction is presented as a small image with a list of available topics.
• Each topic has a sound file that introduces the attraction.
• List of topics are based on the user’s interests.
Gulliver’s Genie (2003)
Gulliver’s Genie: A Multi-Agent System for Ubiquitous Intelligent Content Delivery. G.M.P. O’Hare, M.J. O’Grady, Computer Communications, Vol.26, Issue 11, pp.1177-1187, 2003 Elsevier
BPN Navigation System (2004) o Type: Resource adapting o An entirely system that
combines a desktop route planning, a car navigation system, and a multi-modal in-outdoor pedestrian navigation
o Provide a seamless service for travelers in different situations
Kruger, A., et al (2004), The connected User Interface: Realizing a Personal Situated Navigation System. In IUI2004: International Conference on Intelligent User Interfaces, New York, 161-168
Just-For-Us (2005)
Just-for-Us: A Context-Aware Mobile Information System Facilitating Sociality���Jasper Kjeldskov and Jeni Paay ���
Proceedings of the Mobile Human Computer Interaction, 2005���
• Making the Invisible Visible: Augmenting the user’s physical surroundings
• Supporting Ad-Hoc Communication about Places, Activities, and Time
• Indexing Recommendations and Content to History and Context
• Representing Activities within Proximity and Indexing to Familiar Places
Just-For-Us: Functionality
The System Architecture
NaviTime (2007) Type: Resource adapting Provide users with total navigation support
All mode of transportation such as walking, driving, and riding trains, buses, taxis, and airplanes
Encompasses the entire traveling activity
The best route is calculated based on user’s preference (e.g., route with minimum expenses)
Arikawa, M., Konomi, S., Ohnishi, K. (2007), Navitime: Supporting Pedestrian Navigation in the real world, Pervasive Computing, IEEE,6(3), 21-29
iCity Project (2008) Type: resource adapting An adaptive, social, multi-device
recommender guide The combination of the principles of
adaptation and web 2.0 Allowing users to post new events, rate
existing items, provide comments and judgments to a resource
Provide the adaptive presentation based on the device between desktop and mobile
The recommended items are tailored to individual according to the user model and contextual elements
F. Carmagnola, F. Cena, L.C.O. Cortassa, C. Gena, A. Goy, I. Torre, A. Toso, and F. Vernero, Tag-based user modeling for social multi-device adaptive guides. User Modeling and User-Adapted Interaction (2008)
Sotto Voce Museum Guide Type: Resource adaptive A handheld electronic guidebooks Take into account the special needs of
groups, not individual user By having pictures of the walls presented
on the PDA’s screen and asking from the user to select the exhibit he/she is interested in, by pressing it
Encourage communications among group members by using audio sharing mechanism called “eavesdropping”
Aoki, P. M., Grinter, R. E., Hurst, A., Szymanski, M. H., Thornton, J. D., and Woodruff, A. 2002. Sotto voce: exploring the interplay of conversation and mobile audio spaces. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Changing Our World, Changing Ourselves
Agent Salon Project o A life-like character-based
system for personal guidance o Require explicit personal
interests and rate each exhibit during the tour
o Support face-to-face discussions and exchange of knowledge by tempting users to chat with each other
Sumi, Y., Mase, K. In:Interface Agents that facilitate knowledge interactions between community members. Springer-Verlag (Cognitive Technologies series)(2004) 405-427
Information Kiosk
PEACH Using the virtual character acts as a
tour guide Using “like-o-meter” to collect user
feedback Provide the seamless ubiquitous
presentation between a handheld device and a stationary device
Provide automatically generated, adaptive video documentaries on mobile device
Provide automatically generated post-visit summaries that reflect individual interests of visitors
Stock o., et al (2007), Adaptive, intelligent presentation of information for the museum visitor in PEACH, User Modeling and User-Adapted Interaction , 17, 257-304
Like-o-meter
PhoneGuide Using mobile phones for on-device
object recognition Image classification techniques with
user feedback are used to automatically recognize objects
Provide a visitor with multimedia information
Lawrence Rosenblum and Simon Juliar (2008), Mobile Phone-Enabled Museum Guidance with adaptive classification, IEEE Computer Society, pp. 88-102
Video link
Smart Shopping Assistant (2003) Utilizing plan recognition techniques
(inferring a user’s plan by observing his actions) to aid a user while shopping o Provide product information o Provide product recommendation o Provide product comparison o Provide recipe hints
Tablet PC RFID antenna
Schneider, M., (2003), Towards a transparent proactive user interface for a shopping assistant, In: Workshop on Multi-user and Ubiquitous User Interfaces, pp. 10-15
Metro Future Store (2006) Type: Resource adapted Integrate multiple emerging
technologies into an existing store Electronic shopping lists Provide product information and
navigate customer within a store Recommend promotional
information using video and animation
Smart check out system
Video Links
Kirthi Kalyanam, Rajiv Lal, and Gerd Wolfram (2006), Future Store Technologies and their impact on grocery retailing, In Retailing in the 21st Century, pp.95-112
Magitti • Started as Japanese project, aiming to develop a service
to replace printed city-guides, sponsored by Dai Nippon Printing Co., Ltd.
• Magitti – Activity-centered mobile leisure-time guide. – For young city-travelers (20-30) interested in all kinds of
leisure activities, emphasizing spontaneity rather than fixed and planified sightseeing.
• What does it do? – It first predicts ongoing and future activity based on the
user’s context and models of past behavior, and then – Predicts (and recommends) what information will be
most useful within the predicted activity.
Victoria Bellotti, Bo Begole, Ed H. Chi, Nicolas Ducheneaut, Ji Fang, Ellen Isaacs, Tracy King, Mark W. Newman, Kurt Partridge, Bob Price, Paul Rasmussen, Michael Roberts, Diane J. Schiano, Alan Walendowski: Palo Alto Research Center
Design Requirements
• Context: Field study in Tokyo. • After a study for understanding leisure time
priorities (interviews and mockups, online survey, focus groups, mobile phone diaries, street activity sampling, expert interviews, and informal observation) they obtained the following design requirements: – Relaxation, Serendipity and Spontaneity – Avoidance of Information Overload – Minimal Size (keitai – handhelds) – One-handed operation (commuters on subway)
Magitti Features • Context Awareness:
– It knows about current time, location, weather, store hours, and user patterns.
– It also lets people specify a future context for planning. • Activity Awareness:
– It filters items to recommend based on its user’s inferred or explicitly specified activity modes.
– Five modes were derived from observations in field work: Eating, Shopping, Seeing, Doing, or Reading.
– Each item in the Magitti database is explicitly tagged as being associated with these modes.
• Serendipitous, relaxing experience: – Users need not enter profile, preferences, or queries. – They can rely on context and activity inferencing for Magitti to
continually and automatically update recommendations.
Magitti System Design
• System shows up to 20 recommendations and updates while the user moves Allows
the user to rate
Magitti System Design - II
• Mode 2