Department of Computer Science
Universidad Politécnica de Madrid
Information Agents for Optimal
Repurposing and Personalization
of Web Contents in SemanticsAware Ubiquitous and Mobile
Computing Environments
Fernando Alonso
Sonia Frutos
Miguel Jiménez
Javier Soriano
Tenth International Workshop CIA 2006 on
Cooperative Information Agents
Outline
1. Motivation
2. Repurposing
3. Agent based personalization
4. User profile-awareness
5. Context-awareness
6. Summary & Future Work
Motivation
•
•
•
•
Ubiquitous access to Web
contents
Same contents, different
devices
Web contents are designed for
PCs
Web-enabled mobile devices
have different capabilities:
–
–
–
•
Rendering
Use
Performance
Interoperability and
accessibility to Web contents
and Web applications
–
–
–
Repurposing
Personalization
Semantic description of
contents
Repurposing
Convert the appearance of Web contents
so that they can be transparently accessed
from a wide variety of devices.
• The same content adapted to each device
• Transcoding techniques based on the
syntax of Web content (rendering and
content are mixed in Web pages
nowadays)
• New approaches based on device
independent-definition of Web contents
– Morfeo Mobility Channel
Morfeo Mobility Channel
MyMobileWeb
O. S. Mobility platform that enables
the development of semantics-aware
mobile applications and services and
provides transparent access from
mobile devices.
– Single XML-based language for defining the
renderings (RDL).
– WURFL based
– Design-time adaptation
– Run-time data access and automatic
pagination
– Supports semantic description of interface
and contents
Semantic enrichment of
Web contents
•
•
•
•
The enabler for semantic repurposing and
personalization
Semantic description of user interface and Web
contents
Based on the declarative language RDL used in
Morfeo Mobility Channel
Classical approach
– XML UI Æ Browser Markup
•
Semantic approach
– XML UI + Sem. Bindings Æ Browser Markup + RDF
•
Extended information about Web applications that
can be used for multiple purposes
– Semantic Mobile Bar
– Application Integration
– Personalization & Customization (adaptation
process)
Morfeo SMC
Personalization
Take
into
account
the
user
preferences, navigation context and
device capabilities in the adaptation
process.
• Improve the legibility and usability of Web
contents through mobile devices
• Semantic based adaptation of web contents
• Semantic descriptions are needed about Web
contents
• Syntactic repurposing vs semantic
repurposing
• Personalization is based on:
– User profile awareness
– Navigation context awareness
Agent-based Personalization
Ac
tiv
Br
ow
si
ng
User Profile & Context
Aware Content Repurposing
and Personalization
ity
User profile-Awareness
•User related
knowledge
User
•Long-term interests
Profile
•Short-term interests
(interaction oriented)
•User Habits
Ubiquitous
Users
Nav.
Navigation
Context
context-Awareness
•Time,
•Space and Location,
•Device Capabilities,
•Network (throughput,
connectivity, …),
•Ubiquity, …
Agent-based Personalization
Two pairs of agents
• Balance between privacy,
heavy-height and bandwidthintensive tasks
• Interact with the open
environment
• High level of automation
• Interoperability
User Profile-Awareness
• Information about the user is needed for
optimizing Web contents personalized for
him
• More knowledge about the user implies
more help
• A model about personal information
including:
– Concrete information (date of birth, address,
ID’s … )
– Intangible information (likes, desires … )
• Privacy issues Æ User profile handled by
information agents
Profile Model
Profile ≡ Ši ∃hasCharacteristic.Characteristici
Š j ∃hasInterest.Interest j
Šk ∀hasInterest.(¬Disinterestk )
Šl ∃demands.Thing
Example with user
interests
User1 ≡ ∃hasInterest.(Wine Š (∃hasRegion.Rioja)) Š
∃hasInterest.(¬Wine ‰ ¬(∃hasRegion.RiberaDuero))
TradeService ≡ ∃provides.Thing
RestSrvc1 ≡ ∃offers.(RedWine Š (∃hasRegion.Rioja))
RestSrvc2 ≡ ∃offers.(Wine Š (∃hasRegion.Rioja))
RestSrvc3 ≡ ∃offers.(RedWine Š (∃hasRegion.RiberaDuero))
Example with user
interests
−
UserInterest ≡ ∃hasInterest .Profile
ServiceOffer ≡ ∃offers − .TradeService
How adequate are the services supplied for the user?
• Five compliance levels [Li & Horrocks, 2003]
– Exact UserInterest ≡ ServiceOffer
– PlugIn UserInterest ‹ ServiceOffer
– Subsume ServiceOffer ‹ UserInterest
– Intersection ¬(UserInterest Š SericeOffer ‹⊥)
– Incompatible UserInterest Š ServiceOffer ‹⊥
• Has to be calculated for every pair
<user,tradeservice>
Navigation ContextAwareness
• Context influences Web
browsing activity
– Particularly in mobile
environments
• How to define the context
– Physical information (timing,
geographical inf.)
– Social information (role)
– Device/network capabilities
Example
During a tourist guide someone uses
his mobile device to get information
about the visit, the place, the city…
–
–
–
–
–
Time
Location
Network
Display
Ubiquity
The Context
va
lu
eO
f
ATTRIBUTES
isRelevant
RAS(g)
GOAL
IRAS(g)
The goal is the objective for which the context is
used at any particular time
The attributes describe the context in a ontological
way, ContextAttribute class
–
–
–
–
Name
Needed parameters
Values domain
Multi-valuated
Summary
•
Mobile devices are radically different from desktop
PCs
•
Mobile adaptation of content based in syntax only
produces suboptimal results
•
Semantic annotation in mobile computing software
platforms
•
Method to provide explicit semantics to the Web
contents produced by a Mobility framework
•
Agent architecture as the ideal method for handling
user profile information and navigation contextawareness
•
Agent-driven & semantically-based adaptation
process
Future work
• Dynamic goal discovering
• Defining the user profile
– Integrate folksonomies with the
user profile model
Department of Computer Science
Universidad Politécnica de Madrid
Information Agents for Optimal
Repurposing and Personalization
of Web Contents in SemanticsAware Ubiquitous and Mobile
Computing Environments
Thank you!
Fernando Alonso
Sonia Frutos
Miguel Jiménez
Javier Soriano
mjimenez@pegaso.ls.fi.upm.es
Tenth International Workshop CIA 2006 on
Cooperative Information Agents