Adaptive Hypermedia
Meets Provenance
Evgeny Knutov
Paul De Bra
Mykola Pechenizkiy
GAF project: Generic Adaptation Framework
(project is supported by NWO)
Agenda:
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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:
• Classification of AH
methods and
techniques integrated
with adaptation
process
• Basis for the AHS
layered structure
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GAF layered model:
• 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
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W7 Provenance model:
Where
location
happens in
When
timestamp
occurs at
agent
is involved in
Who
is because of
rationale
Why
is used in
device
Which
leads to
action
How
Event
• W7 provenance model (S. Ram)
• Provenance is information about the origin,
ownership, source, history, lineage and/or derivation of
an information object or data
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Adaptation process:
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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”:
Classification of AH
Methods and
Techniques;
adaptation process
highlights
When?
To What?
What?
How?
Where?
Defining user
(1)
goal
Passing
content to be
rendered and
presented
Aligning goal with
(2)
Domain Model
Initiating adaptation (3)
Presentation Model
(6)
Application Model
User Model
Domain Model
UM-DM
overlay
sustainability
(4)
Adaptation Model
Retrieving/updating
UM state
Retrieving concept
corresponding domain (5)
information (hierarchy,
resources, meta data, etc.)
Context Model
Goal Model
(7)
Invoking
adaptation
methods and
techniques
Interaction
requires reply
Acquiring
resources
(content) for
the concept
(8)
User Context
Defining
usage context
Group
(9)
formation
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Usage Context
Passing data/
control to other
sub-system
Maintaining
and
Acquiring
Adaptive rules
of higher order
Considering
usage context
Maintaining and
updating HOA with
system usage data
Group Model
Legend:
Resource Model
Acquiring user
context
Higher Order Adaptation
Why?
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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 steps
• Explanation: explaining system usage and
adaptation origin
• Usage pattern Analysis
• Reliability 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 triggering
a particular event (evidence of
what has happened)
How?
describing AH methods and
techniques on a conceptual and
implementation level (Adaptive
Engine (AE) functionality);
explains the sequence of eventactions;
describes the semantics of
cause-effect relations
the set of all actions leading up
to the events (keeping track of
the events, and corresponding
action in the system);
describes the syntax of events
and 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 usecases and examples of provenance in AH
• Align adaptation sequence chart with other useradaptive 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
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SLIDES
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AHS evolution:
• Generalize AHS functionality in GAF
• Enhance GAF layered structure with the process
• Generalize adaptation process in GAF
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Use-case: WWW Search sequence chart:
User Profile
AHS
Overlay
Model
Defining User – stating
the query
user goal
Ranking
Passing
content to be
rendered and
presented
Interpreting
Query
(refolmulation,
extern lex., etc.)
Initiating
adaptation
AH
methods and
techniques
Acquiring
resources for
the concepts
/ Department of Computer Science
www
Group
formation
Maintaining
collaborative
profile
User Context
Usage Context
index
Search
Defining the and Result
usage context history
Group Model
Crawler
Resource Model
IP, profile, etc.
Considering
usage context
Adaptation Model
Acquiring user
context
Application Model
Context Model
UM-DM
overlay
sustainability
Invoking
adaptation
Methods and
techniques
Accumulating user
search history
Retrieving/updating
UM state
User Model
Domain Model
Goal Model
parsing query
Retrieving concept
corresponding domain
information (hierarchy,
resources, meta data)
User Interface:
Presenting search
results, snippets,
ranking info., etc.
Presentation Model
Aligning goal with
the Domain
Search
Engine
Maintaining
and
Acquiring
Adaptive rules
of higher order
Maintaining and
updating HOA with
system usage data
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Higher Order Adaptation
Search Query
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Use-case: WWW Search:
• Sequence chart (GAP) compliance with the search
process:
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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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