1. Amel Bouzeghoub Serge Garlatti
Context Modeling
&
Adaptation
Amel Bouzeghoub
Serge Garlatti

2. Outline Context & Context-Awareness General Model of Context-Awareness
Context Modeling
Applications
Context-Aware Learning Systems
Adaptation: Main issues
Adaptation Process and Principles
Mobilearn Project
P-LearNet Project
Conclusion
4th-9th july 2009

3. Is all this information measurable?
Defining Context
Location, identities of nearby people and objects [Schilit and Theimer]
Location, identities of the people around the user, the time of day, season, temperature, etc. [Brown et al.]
The user’s location, environment, identity and time [Ryan et al.]
The user’s emotional state, focus of attention, location and orientation, date and time, objects, and people in the user’s environment [Dey]
The elements of the user’s environment that the user’s computer knows about [Brown]
The situation of the user [Franklin & Flaschbart]
Is all this information necessary?
Is all this information measurable?
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4. Defining Context (cont’d)
Dey defines the context as “any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves.”
Schilit et al. claim that the important aspects of context are: where you are, who you are with, and what resources are nearby. They define context to be the constantly changing execution environment
Computing environment available processors, devices accessible for user input and display, network capacity, connectivity, and costs of computing
User environment location, collection of nearby people, and social situation
Physical environment lighting and noise level
Which aspects of all situations are important ?
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5. Defining Context (cont’d)
Context is the set of environmental states and settings that either determines an application’s behavior or in which an application event occurs and is interesting to the user [Chen]:
Active context: influences the behavior of the application
an application automatically adapts its behavior to discovered context
Passive context: context that is relevant but not critical
an application presents the new or updated context to an interested user or makes the context persistent for the user to retrieve later
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6. Defining Context (cont’d)
Sensor data
Other classifications of context:
Low-level vs High-level context
External (physical)
Context that can be measured by hardware sensors
location, light, sound, movement, touch, temperature, air pressure, etc.
Internal (logical)
Mostly specified by the user or captured monitoring the user’s interaction
the user’s goal, tasks, work context, business processes, the use’s emotional state, etc.
Low-level context
motivational
social
user
location
computing
temporal
high-level context
Context processing
active context
passive context
Context-aware application
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7. Defining Context (cont’d)
3 entities
Places (rooms, buildings, etc.)
People (individuals, groups)
Things (physical objects, computer components, etc.)
Attributes
Identity (each entity has an unique identifier)
Location (an entity’s position, co-location, proximity, etc.)
Status (or activity)
Time (used for timestamps to accurately define situation, ordering events, etc.) …
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8. Challenges
[Roy Campbell]
Context is most useful in dynamic, mobile environments. But what is the relevant information in various situations?
Mobility results in continuous updates of context information. How can we efficiently manage this?
How can we share context?
How do we handle uncertainty of context information?
How do we ensure privacy control and management of context information?
How do we reach a common understanding of implications and semantics of (shared) context information?
Resource restrictions 8
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9. Context-Awareness
“A system is context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user’s task.” [Dey’s definition]
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10. General Model of Context-Awareness
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11. Abstract Layer Architecture
Sensing: numeric observables
Perception: symbolic observables
Situation and context
Applications
Privacy/
Security/
Trust
History
Discovery/Recovery
Usage
Generation
sensors
[J. Coutaz, et al.]
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12. Abstract Layer Architecture (cont’d)
The sensing layer generates numeric observables to determine meaning from numeric observables, the system must perform transformations
Physical sensors
RFID, camera, microphone, accelerometer, GPS, thermometer
Virtual sensors
From software: browsing an electronic calendar, a travel booking system, s, mouse movements, keyboard input
Logical sensors
Combination of physical and virtual sensors
The perception layer is independent of the sensing technology and provides symbolic observables at the appropriate level of abstraction
Changes of Context !!
Most of contextual information changes as time goes on
Context changes can be sensed by, periodic polling, advertising, selective polling
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13. Abstract Layer Architecture (cont’d)
The situation and context layer identifies the current situation and context from observables
The exploitation layer acts as an adapter between the application and the infrastructure. This is where applications express their requests for context services at a high level of abstraction
At every level of abstraction, one must incorporate mechanisms and facilities to support privacy, trust, and security as well as history management and discovery/recovery
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14. Context Modeling
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15. Motivations Context modeling requirements: Formality
Support for efficient reasoning
Support for imperfect context information (imprecise, ambiguous, incomplete information)
Appropriate abstractions to support requirements analysis, design and programming tasks
Support for interoperability
4th-9th july 2009

16. Context Modeling Context Model
Define and store context data in a machine processable form
Context Modeling Approaches
Key-Value Models
Markup Scheme Models
Graphical Models
Object Oriented Models
Logic Based Models
Ontology Based Models
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17. Context Modeling Approaches
Key-Value-Pairs Models [Context Toolkit]
Most simple category of models
Not very efficient for more sophisticated structuring purposes
Only exact matching (set loc=room_134)
No inheritance
Standard Retrieval Method: Linear Search
Markup Scheme Models [Stick-e]
XML-based models
Composite Capabilities/Preference Profile (CC/PP), [W3C, 2004], User Agent Profile (UAProf) encoded in RDF/S [Wapforum, 2001]
Standard Retrieval Method: Markup Query Language
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18. Context Modeling Approaches (cont’d)
Graphical Models [ORM]
UML-like languages (CML)
Particularly useful for structuring, but usually not used on instance level
Standard Retrieval Method: Transformation
Object Oriented Models [Hydrogen]
Intention behind object orientation is (as always) encapsulation and reusability
Standard Retrieval Method: Algorithm
4th-9th july 2009

19. Context Modeling Approaches (cont’d)
Logic Based Models [eWallet – myCampus]
Logic defines conditions on which a concluding expression or fact may be derived from a set of other expressions or facts (reasoning)
→ context is defined as facts, expressions and rules
High degree of formality
Cannot inherently deal with uncertain or conflicting information
Suit better in cases, where we are certain about the quality of the collected data
Standard Retrieval Method: Inference
4th-9th july 2009

20. Context Modeling Approaches (cont’d)
Ontology Based Models [SOCAM, CoBrA, Context Managing Framework]
Ontology used as explicit specification of a shared conceptualization
Context is modeled as concept and facts
Advantages:
formal models that can be
shared
reused,
extended
combined
Standard Retrieval Method: Reasoning
4th-9th july 2009

21. Summary Approach Requirements dc pv qua inc for app Key-value models -
dc: distributed composition
pv: partial validation
qua: quality of information
Inc: incompleteness
and ambiguity
app: applicability to
existing env.
for: level of formality
Approach
Requirements dc pv
qua
inc
for
app
Key-value models - +
Markup scheme models ++
Graphical models
OO models
Logic based models
Ontology based models
4th-9th july 2009

22. Applications
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23. Applications - Efficient UI
[Team Edward : Hee-Jung Yang and Hyeong-Ho Yoo (2005)]
More efficient UI as context changes
Brighter display in dark place
Simplified text when I am moving
normal
dark place & user is moving
4th-9th july 2009

24. Applications - Efficient UI (cont’d)
Show only important part of clip for poor network bandwidth or small display
Different menu for different place
Sort people list by distance or show on a map
big display
small display
Depend on user’s preference
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25. Applications - Reconfiguration
Optimize internal components
Choose the fastest connection to server
Print with the closest printer
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26. Applications - Triggering
Trigger useful information relevant to current context
Car navigation system
Explanation about the place where user travels
Show cooking guide in kitchen, show work files in office
Reminder for specified context
When I next meet Serge, tell him ...
When next at a market, buy ...
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27. Applications – Memory Retrieval
Save contexts of each event and retrieve them later
Who were the girls with Serge at the last meeting in Paris?
What was the note I made at a meeting last June in this conference room? I remember Bill and John were there.
4th-9th july 2009

28. Applications – Memory Retrieval (cont’d)
Object is defined by relative context
Filename is the context in which it is made
We don’t have to remember the filename
Interrupted task is resumed if the context revived
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29. Applications – Sharing Experience
Refer other people's contexts
Travelers download my contexts of my trip
Broadcast my context
I send to neighbors the information about cheap theatres
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30. Context-Aware Learning Systems
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31. Other definitions…
Ogata, & Yano : “ Ubiquitous learning is characterized by providing intuitive ways for identifying right collaborators, right contents and right services in the right place at the right time based on learners surrouding context »
Derntl & Hummel: « learning context is used to describe the current situation of a person related to a learning activity. In addition to attributes relying on the physical world model »
A. Kurti & M. Milrad: « information and content in use to support a specific activity (being individual or collaborative) in a particular physical environment ».
Adaptation
Learner-centered +
Environmental factors (e.g. location, time of the day, delivery media)
Goal: capturing and usage of contextual information in context-aware learning environments
4th-9th july 2009

32. Research Questions
How to model mobile learning context considering individual tasks, community activities, and current environment?
How to use context in a particular mobile learning scenario in order to provide adaptation to users?
How to develop a flexible system architecture for adaptive activity-based vs situation-based learning?
4th-9th july 2009

33. Adaptation
4th-9th july 2009

34. Main Issues Context-Awareness and Adaptation
At different levels in the global architecture
HCI components
Educational and semantic components
Middleware components
Network components
On Mobile Learning

35. Main Issues Context properties Dynamic “Context-as-construct”.
Context settings could be “unpredictable” because it is dynamically created and modified through continual interactions with users and environment.
On Mobile Learning

36. Main issues Context-Awareness and Adaptation
Select dynamically the relevant resources
Teachers, Learners, Communities,
HCI components,
Scenarios, activities, multimedia documents
Middleware components, web services
Network components, etc.
According to the current situation
As a subset of the context model
On Mobile Learning

37. Adaptation Process and Principles
Context-Awareness and Adaptation
Resource model assumptions
A set of structured features from
« External » resources
A metadata schema having LOM as a subset:
General, technical,
Pedagogical, classification,
Meta metadata, rights,
Version, etc.
« Internal » resources
A set of features describing a learning object
On Mobile Learning

38. Adaptation Process and Principles
Context-Awareness and Adaptation
Context model assumptions: a set of structured features
scenario, activity,
Learner, teacher, Community,
Location, time, network,
Device,
Tools, etc.
On Mobile Learning

39. Adaptation Process and Principles
Context and Adaptation Mangement Process
On Mobile Learning

40. Adaptation Process and Principles
1) Resource Retrieval
Resources
Multimedia documents: images, movies, texts, sounds, etc.
Activities, scenarios, Web services, Web page patterns,
HCI components, middleware components, etc.
Query
 Result: a set of resources
On Mobile Learning

41. Adaptation Process and Principles
2) Resource retrieval refinement
Filtering process
Matching context model against resource metadata or indexing
Outcome, at least, two classes: « Good » and « Bad » Or up to 5 classes (ressource clustering)
Mutually exclusive equivalence classes!!!!!!!
3) Applying and adaptation method
Annotation, hiding, sorting or ranking, etc.
On Mobile Learning

42. according to resource category!
Adaptation Process and Principles
according to resource category!
On Mobile Learning

43. Adaptation Process and Principles
Unfortunately
Context settings could be “unpredictable”
Not really possible to deal with!
Consequences
Membership rules combine contextual and metadata properties to classify resources
What happens when some properties are not available?
Impossible to compute membership?
On Mobile Learning

44. Adaptation Process and Principles
How to manage context features to have flexibility as much as possible?
Two Case Studies
Mobilearn
P-LearNet
On Mobile Learning

45. Mobilearn Project

46. Mobilearn Project Goals
Produce an integrated architecture for learners with mobile devices
Support for collaborative learning
Adaptive human interface
Context-aware presentation of content, options and services to support learning activities
On Mobile Learning

47. Mobilearn Project Context Hierarchy Scenarios
Determine the relevant context elements
To match the context-awareness of the learner’s needs
Context
What's going over time
Context State
Elements (currently present) from the Learning and Setting at one particular point in time, space, or goal sequence
Context Substate
Elements from the Learner and Setting that are relevant to the current focus of learning and desired level of context awareness
Context Feature
Context Feature
Context Feature
Context Feature
On Mobile Learning

48. Mobilearn Project
Context awareness architecture
On Mobile Learning

49. Mobilearn Project Basis Cycle of operation
1) Gathering and input of context metadata
2) Construction of context substate
3) Exclusion of unsuitable content
4) Ranking of remaining content
5) Output of ranked list of content
On Mobile Learning

50. Mobilearn Project Context feature belong to two types Excluders
Items of content, deemed entirely inapropriate for the current context are excluded
Belong to class « Bad » and are hidden
Or Rankers
Increments the score of each content item that has metadata matching the value of any particular context feature
The size of increment depends on the salience value associated to the considered context feature
On Mobile Learning

51. Mobilearn Project
On Mobile Learning

52. Mobilearn Project Context awareness and adaptation
As the adaptation process is dedicated to a single feature, it is possible to deal with almost « unpredictable » context settings.
On Mobile Learning

53. P-LearNet Project
On Mobile Learning

54. P-LearNet and e-retail requirements
What activities I can do in the selling situation?
Need to model activities (scenario)
How can I get supports or helps?
How can I realize an activity when the working situation changes?
-Need to integrate learning and working activities
-Continuous professional learning at the workplace or elsewhere
What and how can I learn during working activities?
Seller
Need to achieve an activity in different contexts, across different contexts
Increasing the system capability to get information about physical and social selling environment to enrich learning at the workplace to improve the market

55. Context modeling A context management model A context model,
A context metadata schema
A set of situations
A situation: a partial instantiation of the context model consisting of the available features
Organized in historical dependencies
On Mobile Learning

56. Goals
Designing a context-aware and adaptive mechanism to select relevant resources to achieve activities
Finding relevant resources according to the current situation
Modeling integrated context-aware learning and working scenarios in the workplace
page 56

57. Two Adaptation Strategies
Situation-based Learning
Passive Adaptation
Proactive Adaptation
Recommendation system
Depending on learner situation
proposes right contents, right services, right activities, right collaborators in the right place at the right time
Activity-based Learning
Task/method paradigm
On Mobile Learning

59. Situation-based Learning
User current situation at in
nearBy
hasSituation
uses in
do(role)
collaborate
nearBy 59
User
Location
Activity
Device
Environment
Time
On Mobile Learning 59

60. Situation-based Learning
Passive adaptation
Reduces the number of resources according to user current situation
Uses filters: user knowledge, profile and preferences
Proactive adaptation
Allows an active recommendation of resources without user intervention simply by detecting predefined events or system events
Uses ECA rules (Event/Condition/Action).
Authors describe resource behaviour depending on events that occur during the situation
Prototypical situations, hierarchical organization
Authors have to provide pedagogical rules for the course or to precise which rules to use among the set of existing rules.
Example: in such situation, (situation in which the learner encounters difficulties and needs help), the author may indicate which action is needed to help the learner: provide an easier or more detailed resource
On Mobile Learning

61. Situation-based Learning: Passive Adaptation
Resource Retrieval and Adaptation
Input
content :
Resources
Context Metadata
Current situation
Evaluation
Filtering
Knowledge
Preferences
Relevant content
Ranking /
Annotation
Current Situation
Passive Adaptation
User Queries
Weighted content
On Mobile Learning

62. Situation-based Learning: Proactive Adaptation
Provides the relevant esources according to current situation
Events:
Matching
Prototypical situations
Evaluation
Filtering
Ranking
Annotation
Matched
situations
Current situation
Context Metadata
Weighted
content
Relevant ,
Passive Adaptation
Proactive Adaptation
ECA / Situational rules
Pedagogical rules
Searching
Resource
Resources
On Mobile Learning

63. Activity-based Learning
Working and learning activities are intertwined in the workplace
How to model integrated learning and working activities in workplace – e-retail system?
Seamless Learning and Working
Achieve activities according to the current situation
New situation  New way to achieve an activity?
Scenarios for modeling activities in context and across contexts
On Mobile Learning

64. Activity-based Learning
Context-aware scenarios
Context-aware learning scenarios at workplace is represented by a hierarchical task model
The task/method paradigm
Tasks:
Represent activities and sub-activities
An abstract task is composed of sub-tasks
An atomic task can be achieved by a simple procedure and can not be composed of sub-tasks
On Mobile Learning

65. Activity-based Learning
Context-aware scenarios
Methods: represent a way to achieve a given task according to a context
Methods described by contextual features
(Web) Services/ resources described by metadata
realized by
Resource requirement
Method1
Retrieval-Matching
Task
(Web) Service requirement
Method2
Method3
function
specification
SubTask1
Method4
Control
structure
SubTask2
Define a decomposition of a task into subtasks
On Mobile Learning

66. Activity-based Learning
On Mobile Learning

67. Activity-based Learning
Select the relevant methods to achieve a given task according to the current situation
On Mobile Learning

68. Activity-based Learning
Service retrieval and adaptation
On Mobile Learning
Page 16

69. Conclusion Some Open Issues
How to manage context features and adaptation process
How to manage adaptation at all levels?
HCI components
Educational and semantic components
Middleware components
Network components
On Mobile Learning