Amel Bouzeghoub Serge Garlatti Context Modeling & Adaptation

Amel Bouzeghoub

Serge Garlatti

Context Modeling&Adaptation

Mobile Learning Summer School - Brest 4th-9th july 2009Page 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


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 inform

ation measurable?


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 im

portant ?



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



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.

social

temporal

motivational

location

user

Sensor data

computing

Low-levelcontext

Context processing

high-levelcontext

Context-aware application

activecontext

passivecontext



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.)• …

Mobile Learning Summer School - Brest 4th-9th july 2009Page 8 8

Challenges

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

[Roy Campbell]


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]


General Model of Context-Awareness


Abstract Layer Architecture

Generation

Usage

Sensing: numeric observables

Perception: symbolic observables

Situation and context

Applications Privacy/Security/Trust

History Discovery/Recovery

[J. Coutaz, et al.]

sensors


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,

emails, 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


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


Context Modeling


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


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


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


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



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



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


Summary

Approach Requirements

dc pv qua inc for app

Key-value models - - - - - +

Markup scheme models

+ ++ - - + ++

Graphical models - - + - + +

OO models ++ + + + + +

Logic based models ++ - - - ++ -

Ontology based models

++ ++ + + ++ +

dc: distributed compositionpv: partial validation

qua: quality of informationInc: incompleteness and ambiguity

app: applicability to existing env. for: level of formality


Applications


Applications - Efficient UI

More efficient UI as context changes• Brighter display in dark place• Simplified text when I am moving

normal dark place & user is moving

[Team Edward : Hee-Jung Yang and Hyeong-Ho Yoo (2005)]


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


Applications - Reconfiguration

Optimize internal components• Choose the fastest connection to server• Print with the closest printer


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 ...


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.


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


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


Context-Aware Learning Systems


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


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?

Research Questions


Adaptation

Mobile Learning Summer School - Brest

Context-Awareness and Adaptation• At different levels in the global architecture

- HCI components- Educational and semantic components- Middleware components- Network components

page 34

Main Issues

On Mobile Learning


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.

page 35 On Mobile Learning


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



Adaptation Process and Principles

On Mobile Learningpage 37



Context-Awareness and Adaptation• Context model assumptions: a set of structured

features- scenario, activity, - Learner, teacher, Community, - Location, time, network, - Device, - Tools, etc.




page 39

Context and Adaptation Mangement Process

On Mobile Learning



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




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.



according to resource category!

page 42

Input content:

Resources

Metadata Features

Context Features

Clustering Filtering

Relevant content

{«Good» «Bad»}

Ranking/Annotation

Situation

Adaptation process

«Average»

On Mobile Learning




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?




How to manage context features to have flexibility as much as possible?

Two Case Studies• Mobilearn• P-LearNet



Mobilearn Project


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



Context Hierarchy• Scenarios

- Determine the relevant context elements

- To match the context-awareness of the learner’s needs

Mobilearn Project

page 47

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


Mobilearn Project

Context awareness architecture



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



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



Mobilearn Project

On Mobile LearningPage 51

Resources

Metadata / indexing

Context Substate

Excluders Filtering

Classified content Relevant content

{«Good» - «Bad»}

Rankers

Context substate

Adaptation process


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.



P-LearNet Project



P-LearNet and e-retail requirements

How can I get supports or helps?

What activities I can do in the selling situation?

How can I realize an activity when the working situation changes?What and how

can I learn during working activities?

Need to model activities (scenario)Need to model activities (scenario)

Need to achieve an activity in different contexts, across different contexts

Need to achieve an activity in different contexts, across different contexts

-Need to integrate learning and working activities-Continuous professional learning at the workplace or elsewhere

-Need to integrate learning and working activities-Continuous professional learning at the workplace or elsewhere

SellerSeller

Increasing the system capability to get information about physical Increasing the system capability to get information about physical and social selling environment to enrich learning at the workplace to and social selling environment to enrich learning at the workplace to improve the marketimprove the market

page 54


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 LearningPage 55


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


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



Situation-based Learning

59Location

Activity Device Environment

User Time

innearBy

usesdo(role)

User current situation

in

at

collaboratenearBy

hasSituation

On Mobile Learning


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

Mobile Learning Summer School - BrestPage 61

Situation-based Learning: Passive Adaptation

Input

content:

Resources

Context Metadata

Current situation

EvaluationFilteringKnowledgePreferences

Relevant content

Ranking/

Annotation

Current Situation

Passive Adaptation

User Queries

Weighted content

On Mobile Learning

Resource Retrieval and Adaptation

Mobile Learning Summer School - BrestPage 62

Situation-based Learning: Proactive Adaptation

Events: Matching

Prototypical situations

Evaluation Filtering RankingAnnotation

Matched

situations

Current situation Current situation

Context Metadata

Weighted

content Relevant

content

Current situation

,

,

Passive Adaptation

Proactive Adaptation

ECA / Situational rulesPedagogical rules

Searching Resource

Resources

On Mobile Learning

Provides the relevant esources according to current situation


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




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




Context-aware scenarios- Methods: represent a way to achieve a given task

according to a context-

Task

Method1

Method2

Method3

realized by

Method4

Resource requirement

(Web) Service requirement

function specification

Control structure

Retrieval-MatchingRetrieval-Matching

Methods described by contextual features (Web) Services/ resources

described by metadata

SubTask1

SubTask2Define a decomposition of a task into subtasks



Learning task

Professional task

Mixed task

Legend: S.1.3Sale assistance in situation

M13

Context descriptor:-Role = {Saleman}-Location = {Shop}

S.3_T.1Preparing for the sale

S.3_T.2Finalizing the sale

M132

Context descriptor: (the sale with customers)-Role = {Saleman}-CollaboratorRole = {Customer}-DeviceType ={PTA, Smartphone}-NetworkType = {Wifi, Bluetooth}

M131

Context descriptor: (a saleman without customer)-Role = {Saleman}

-DeviceType = {PTA, Smartphone}-NetworkType = {Wifi, Bluetooth, GMS

Location = {Shelve}}

M133

Context descriptor: (customers are detected nearly a LCD screen)-Role = {Saleman}-CollaboratorDeviceType = {LCD Screen}-CollaboratorRole = {Customer}-DeviceType ={PTA, Smartphone}-NetworkType = {Wifi, Bluetooth}

S.3_T.1.3Identify the

client

M1321

S.3_T.1.4Search and

deliver information of products to the client

M1322

S.3_T.1.8Switch to the supervisory mode (join PTA with

LCD)

S.3_T.1.9Visualize the

summarization table of selected products

S.3_T.1.10Dialog with client on a

screen LCD

S.3_T.1.1Verify the

information about the labeling of products

S.3_T.1.5Get helps

form colleagues or experts

M1323

M1311

{SEQ(S.3_T.1, S.3_T.2)}

{SEQ(S.3_T.1.3, PAR(S.3_T.1.4, S.3_T.1.2, S.3_T.1.6, OPT(S.3_T.1.5)))}

Method

{PAR(S.3_T.1.1, S.3_T.1.2)}

{SEQ(S.3_T.1.3, PAR(S.3_T.1.4, S.3_T.1.2, S.3_T.1.6, OPT(S.3_T.1.5)),SEQ(S.3_T.1.7, SEQ(S.3_T8, PAR(S.3_T.1.9, S.3_T.1.10))))}

M1332

M1333M1334

S.3_T.1.2Revise the

knowledge of products

M1312

S.3_T.1.7Ask for an

interaction of the screen

LCD

M1331

S.3_T.1.6Consult to

FAQ

M1324



Mobile Learning Summer School - BrestPage67

Select the relevant methods to achieve a given task according to the current situation

Input content:

(Methods)

Metadata/ indexing(Context descriptor/Service description)

Situation(with transitory features)

EvaluationClassification Filtering

Classified content Relevant content

{«Good» - «Bad»}

Ranking/Annotation

Situation(with permanent features)

Adaptation process


On Mobile Learning



Service requirement specification

Matching

Metadata/Service description

Evaluation/Classification Filtering Ranking

Matchedservices

Domain ontology Current situation

Metadata/Service descriptionClassified

services Relevantservices

Current situation(permanent

features)

Service Invocation, Orchestration, Choreography

and Execution Subsystem

Adaptation

Service retrieval and adaptation

Page 16On Mobile Learningpage 68


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


Documents

Amel Bouzeghoub Serge Garlatti Context Modeling & Adaptation