Adaptive Hypermedia Adaptive Hypermedia Meets ProvenanceMeets Provenance

Evgeny Knutov Evgeny Knutov Paul De BraPaul De BraMykola PechenizkiyMykola Pechenizkiy

GAF project: Generic Adaptation FrameworkGAF project: Generic Adaptation Framework

(project is supported by(project is supported by NWONWO)

Agenda:

• Adaptive Hypermedia classification and Adaptation process• GAF generic adaptation framework (layered model)• Provenance modeling (W7)• GAF sequence chart, key elements• AH model meets Provenance model• Issues and Prospective Solutions• Conclusions

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Motivating examples:

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Classification of AH methods and techniques; adaptation process highlights:

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• Classification of AH methods and techniques integrated with adaptation process

• Basis for the AHS layered structure

GAF layered model:

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• GAF aligns the order of the layers in the system according to the classification of AH methods and techniques

• Rotate layered structure of GAF and match with adaptation process flowcharts

GAF layered structure

W7 Provenance model:

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Event

is because of

is used in

leads to

happens in

occurs at

is involved in

location

timestamp

agent

rationale

device

action

Where

When

Who

Why

Which

How

• W7 provenance model (S. Ram)

• Provenance is information about the origin, ownership, source, history, lineage and/or derivation of an information object or data

Adaptation process:

• Generic representation of the process• Aligned it with the traditional ‘adaptation questions’• Align the layers of AHS in a sequence chart• Matched flow and sequence process charts• Reference Adaptation Process• Aligned with the Provenance Model

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GAF “sequence chart”:

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Goa

l Mod

el

D

omai

n M

odel

Use

r M

odel

Con

text

Mod

el

Res

ourc

e M

odel

App

licat

ion

Mod

el

G

roup

Mod

el

Ada

ptat

ion

Mod

el

Pre

sent

atio

n M

odel

H

ighe

r O

rder

Ada

ptat

ion

Use

r C

onte

xt

U

sage

Con

text

Group formation

Defining usage context

Acquiring user context

UM-DM overlay

sustainability

Acquiring resources

(content) for the concept

Defining user goal

Interaction requires reply

Passing data/control to other

sub-system

Aligning goal with Domain Model

Considering usage context

Passing content to be rendered and

presented

Maintaining and

AcquiringAdaptive rules of higher order

Initiating adaptation

Invoking adaptation

methods and techniques

Retrieving/updating UM state

Maintaining and updating HOA with system usage data

Retrieving concept corresponding domain information (hierarchy,

resources, meta data, etc.)

Legend:

Why? What? To What?

Classification of AH Methods and Techniques;

adaptation process highlights

How?When?

Where?

(1)

(2)

(3)

(5)

(4)

(8)

(9)

(6)

(7)

Key elements of GAF sequence chart:

• Layered structure preserved in a “sequence”

• Layers aligned with adaptation/provenance questions

• Layers aligned with process and flowchart

• Layers determine (de) composition of the GAF model

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AH meets Provenance:

• Adaptation: provenance data is used by AE to determine adaptation determine adaptation steps

• Explanation: explaining explaining system usage and adaptationadaptation origin

• Usage pattern AnalysisAnalysis• ReliabilityReliability of the AH system• Semantics: expanding the description of the data to

what is answered by the question• Process and Pipeline centric provenance for

Adaptation process

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AH meets Provenance (cont.):

Question AHS Provenance model

Why? stating the adaptation goal(s)(might be a domain concept,representing either a new goal to follow or a sequence of concepts)

the set of reasons for triggeringa particular event (evidence ofwhat has happened)

How? describing AH methods andtechniques on a conceptual and implementation level (Adaptive Engine (AE) functionality); explains the sequence of event- actions;describes the semantics ofcause-effect relations

the set of all actions leading upto the events (keeping track ofthe events, and correspondingaction in the system);describes the syntax of eventsand actions recorded

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Provenance Issues and Prospective Solutions:

• Harvesting issues

GAF distinguishes AH layers, questions and data

• Understanding the semantics of provenance

Matched AH and provenance question

• Diversity of data types and many places of origin

GAF structure and process (de)composition

• Storing, Retrieving and Analysis

Facilitated by versioning techniques in AH

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Conclusions:

• AHS provenance modeling (complimentary features description)

• Provide richer User experience, more sophisticated adaptation and recommendation techniques based on the data provenance information

• Conformity of the adaptation process and provenance model

• Layered process-based (de)composition of an adaptive system

• Building Block of a User-Adaptive System process

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Further work:

• Elaborate process description and extend generic adaptation process emphasizing particular use-cases and examples of provenance in AH

• Align adaptation sequence chart with other user-adaptive systems (e.g. Recommender systems, Adaptive Web search), show

• Emphasize interoperability of the AH developments in the context of provenance (e.g. open corpus adaptation, higher order adaptation, etc.)

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Thanks!and

Questions?

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BACKUP SLIDES

AHS evolution:

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• Generalize AHS functionality in GAF• Enhance GAF layered structure with the process• Generalize adaptation process in GAF

Use-case: WWW Search sequence chart:

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Go

al M

ode

l

D

o mai

n M

ode

l

Us e

r M

ode

l

C

o nte

x t M

ode

l

Re s

ourc

e M

od e

l

Ap

plic

a tio

n M

ode

l

Gr o

up M

odel

Ad

apta

tion

Mo d

el

Pr e

sen t

atio

n M

ode

l

Hi g

her

Ord

er A

dap t

atio

n

Us e

r C

ont

e xt

U

s age

Co

n tex

t

parsing query

Group formation

Defining the usage context

Acquiring user context

UM-DM overlay

sustainability

Acquiring resources for the concepts

Defining user goal

Aligning goal with the Domain

Considering usage context

Passing content to be rendered and

presented

Maintaining and

AcquiringAdaptive rules of higher order

Initiating adaptation

Invoking adaptation

Methods and techniques

Retrieving/updating UM state

Maintaining and updating HOA with system usage data

Retrieving concept corresponding domain information (hierarchy, resources, meta data)

Crawler

index

User – stating the query

User Profile

IP, profile, etc.

www

Search and Result

history

Ranking User Interface:Presenting search results, snippets, ranking info., etc.

Search Engine

Search Query

Interpreting Query

(refolmulation, extern lex., etc.)

Accumulating user search history

Maintaining collaborative

profile

AHS OverlayModel

AH methods andtechniques

Use-case: WWW Search:

• Sequence chart (GAP) compliance with the search process:• Goal Model – defines search query

• Domain Model – defines search index

• Resource model - WWW

• Context Models – defines user and usage context properties (IP, user profile, etc.)

• Group Model – defines user collaborative profile

• Adaptation and Application models – define search engine and ranking mechanisms

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