putting mobile services into contextdynamic context-aware personalisation for smart services s....

Putting Mobile Services into Context Dynamic Context-aware Personalisation for Smart Services

Dynamic Context-aware Personalisation for Smart

Services

S. Gallacher, E. Papadopoulou, N.K.Taylor, M.H.WilliamsHeriot-Watt University, Edinburgh

Future Network & Mobile Summit 2011Workshop on Putting Mobile Services into Context

Warsaw 14th June 2011


Overview

Background - PERSIST and SOCIETIES What is Personalisation? Personalisation in PERSIST and SOCIETIES Conclusion


PERSIST

PERsonal Self-Improving SmarT Spaces Bridging the gap between fixed smart spaces and

mobile pervasiveness.

Personal Smart Space (PSS) Personal Area Network of Devices Owned by person or legal entity Can be mobile or fixed Can interact with other PSSs to share resources and

information


SOCIETIES

Self Orchestrating CommunIty ambiEnT IntelligEnce Spaces

Integrating pervasive systems behaviour with social computing.

Community Smart Space (CSS) For both individuals and communities (static and

dynamic) Provides enhanced user experience Encompasses pro-active smart space behaviour Includes dynamic sharing of community resources


WHAT IS PERSONALISATION?

PERSONALISATION IS the process of adapting the behaviour of a

system to match the needs and preferences of the user.

MAKES a system behave differently for different users or for the same user in different contexts.

INCLUDES the way a system appears to the user and the effect on decision making (e.g. services selected).



PERSONALISATION Affects the way the overall system behaves,

e.g. Devices or services it selects. User Identity (VID, DPI) selected for particular service. Pro-active actions taken.

Affects the way individual services behave, e.g.

Parameters tailoring services to user’s needs.



PERSONALISATION Is generally context-dependent. Most important factor is location – preferences at

home, at work, in town, …. Another important factor is the presence of other

people – one’s boss, one’s family, no one. Other factors include current task, mood, …



EXAMPLES OF PERSONALISATION When the user requests a news service, selecting an

appropriate one depending on whether one is at home, at work, in town.

Automatically turning one’s mobile phone to mute when one enters a lecture room.

When the user requests any service, selecting an appropriate virtual identity to use with the service.

Alerting one to the fact that a friend is nearby. Triggering a service to switch on the heating at home as

one leaves work.



DYNAMIC CONTEXT-AWARE PERSONALISATION When a change is detected in the user’s context,

this may affect the preferences for a running service.

E.g. “Automatically turning one’s mobile phone to mute when one enters a lecture room”

If the presence of other people changes, one may want one’s display to change.

…


PERSONALISATION IN DIFFERENT COMMUNITIES

Term PERSONALISATION is interpreted differently by different communities.

INTELLIGENT TUTORING: tracks state of user’s knowledge and adjusts selection (and presentation) of educational material accordingly.

WEB BROWSING: affects screen layout, preferred urls, etc.

PERVASIVE SYSTEMS: affects selection and execution of services, and their adaptation according to user’s needs and preferences.


PERSONALISATION AND USER MODELLING

In order to personalise any system or service one must have some representation of the user’s needs and preferences This can take various forms:

List of attribute-value pairs. If-then rules. Neural net. Bayesian network. …


DIFFERENT USER MODELS FOR DIFFERENT APPLICATIONS

Different applications have different requirements and hence might prefer different forms of user model. E.g.:

INTELLIGENT TUTORING. Must keep track of state of user’s knowledge about a

particular subject and prefs re material delivery. Can be dealt with by set of attr-value pairs that change

incrementally. PERVASIVE SYSTEMS.

Much more complex. Selection, execution and adaptation of services are all

context-dependent.


Personalisation and PSSs

A PSS (Personal Smart Space) consists of a collection of devices linked by a network.

A PSS may be fixed or mobile. A PSS has a set of user preferences that

represent the wishes of its owner. When one PSSs meets another, they may share

information and services. User preferences are used to adapt the behaviour

of the system when this happens.


Personalisation in PERSIST

STRATEGIES USED TO HANDLE DIFFERENT ASPECTS:

Rule-based user preferences used to represent preferences that the user can see and change.

Neural nets developed as a supplement to rule-based preferences.

Bayesian networks used to infer context attributes relating to the user.

This talk will focus on rule-based preferences.


FORMAT OF SIMPLE USER PREFERENCES:

IF-THEN-ELSE Rules

Outcome depends on user context

Example:IF location = “work” AND status = “busy”THENcall_action = “block”



LearningPersonalisation

Preference Merger

Preference Manager

Preference Condition Monitor

User Intent Prediction

User Intent Discovery

C45LearningManager

Sequence Learning Manager

Bayesian Learning Manager

Incremental Learning

Algorithms

Proactivity

Decision Maker

Decision Implementer

Conflict Resolution


3 Main components: Personalisation, Proactivity & Learning



Personalisation component includes 2 streams: - User intent- User preferences


Implicit Profile Management

Monitor User Behaviour Create User Behaviour History

Extract user preferences and tasks Execute learning algorithms

Update knowledge base Merge new learnt behaviours

Monitor environment and predict outcomes Apply outcomes to personalise resources Respond to user feedback


Event Manager

Preference

Merging

Learning Manager

Context HistoryMgmt

Context Broker

Context Database

Context History

Database

UIM Event

• Increase counter by 1

If counter >=2Trigger Learning Cycle

Request History set

Run Learning Cycle

ReturnHistory set

Retrieve Existing Preferences

Preference

Manager

Merge New and Existing Preferences

ReturnExisting Preferences

Store New Preferences

UpdatedPreferences

PCM

Send Event to Notify PCM

Request Updated Preference Information

Add Information to Tables and register for context events

Learning User Preferences


SOCIETIES

Within SOCIETIES personalisation will follow similar pattern:

Use of preferences to determine which identity to use when starting services.

Dynamic personalisation of individual services from user preferences – both pervasive and social networking.

Proactive action on the user’s behalf – e.g. prompting the creation of communities dynamically when relevant.

Determining of user intent and using this to predict future actions.


Conclusion Dynamic Context-Aware Personalisation involves a

number of functions: Constantly monitor user behaviour and context to identify

when proactive action is required. When a service starts execution, evaluate user

preferences & apply outcomes to personalise resources. Provide user with means to intervene. Monitor context changes to determine when changes to

preferences need to be applied. Accumulate a history of user behaviour and context. Apply learning algorithms to this to extract user

preferences and tasks. Merge new learnt behaviours and keep knowledge base

up to date. Respond to user feedback


Thank you!

... any questions?


PSS Platform

putting mobile services into contextdynamic context-aware personalisation for smart services s....

Documents

mobile services

smart services personalisation

execution of services

adaptation of services

examples of personalisation

users context

way individual services

mobile pervasiveness