SYSTEMATIC THOUGHT LEADERSHIP FOR INNOVATIVE BUSINESS A User Interface Adaptation Architecture for Rich Internet Applications ESWC 2008 Kay-Uwe Schmidt,

SYSTEMATIC THOUGHT LEADERSHIP FOR INNOVATIVE BUSINESS

A User Interface Adaptation Architecture forRich Internet ApplicationsESWC 2008

Kay-Uwe Schmidt, SAP Research

05.06.2008

Addl. Authors SAP: Jörg Dörflinger, Tirdad Rahmani, Mehdi Sahbi and Susan Marie ThomasAddl. Authors FZI: Ljiljana Stojanovic

© SAP 2008 / Kay-Uwe Schmidt / Page 2

1. The Evolution of Rule-based Web Applications

2. The Adaptation Framework

3. Evaluation and Conclusions

Agenda


From Server- to Client-sideAdaptive Hypermedia Systems (AHSs)

Server

Web Application Server

BusinessRulesEngine

Presentation Logic

Business Logic

Business Rules

Browser

Plain HTML Rendering

Server


BusinessRulesEngine

Business Logic

Business Rules

Browser

Rich Client Engine

Presentation Logic

Server


BusinessRulesEngine

Business Logic

Business Rules

Browser

Rich Client Engine

ECARule Engine

Presentation Logic

Presentation Rules

Web Page Paradigm Rich Internet Applications Rule-enabled Rich Internet Applications

Traditional adaptation strategies have been intensively studied

Web Page Paradigm: Every Web page in a series of pages is downloaded separately.

Conventional architecture: tracking of user clicks, the user modeling, as well as the adaptation take place on the server.

Limited user tracking possibilities User requests seen by the server Subset of user clicks

Adaptation only on behalf of an explicit user request

On-the-fly adaptation not obtainable



Server


BusinessRulesEngine

Presentation Logic

Business Logic

Business Rules

Browser


Server


BusinessRulesEngine

Business Logic

Business Rules

Browser

Rich Client Engine

Presentation Logic

Server


BusinessRulesEngine

Business Logic

Business Rules

Browser

Rich Client Engine

ECARule Engine

Presentation Logic

Presentation Rules


RIAs / AJAX New user tracking

possibilities New user interface

adaptation possibilities

Look and feel of desktop applications

Highly responsive user interfaces

Adaptation rules still on the server

On-the-fly adaptation not obtainable



Server


BusinessRulesEngine

Presentation Logic

Business Logic

Business Rules

Browser


Server


BusinessRulesEngine

Business Logic

Business Rules

Browser

Rich Client Engine

Presentation Logic

Server


BusinessRulesEngine

Business Logic

Business Rules

Browser

Rich Client Engine

ECARule Engine

Presentation Logic

Presentation Rules


Client-side rule processing Reduction of client-server-communication to a

minimum Enhanced user tracking capabilities In-time response to user actions

On-the-fly adaptation is obtainable





Agenda


Adaptation Framework

Holistic framework covering the whole adaptation cycle Obtaining adaptation rules and user modeling Transformation of rules and ontologies into a client-side readable format Client-side user model evaluation and rule execution

On-the-fly user interface adaptation

Run-timeDesign-time

RuleExecution

UserTracking

PortalAdaptation

RuleEvaluation

User Model

RuleDesign

Portal Annotation

Ontology Transformator

Semantic WebUsage Mining

User Model Transfer

Ontology Transfer

Adaptation Rules

Modeling Cycle Adaptation Cycle

Transfer Cycle


Ontology Creation and Portal Annotation

Adaptation rules: declarative adaptation logic based on the user model (ontologies)

Ontologies: domain ontologies, RIA ontology, annotation knowledge base

Coherent tool combining learning, refinement and annotation

Run-timeDesign-time

RuleDesign

Portal Annotation



Adaptation Rules

Modeling Cycle


Obtaining the Adaptation Rules

Association Rules: Algorithm: FP-Growth Tool: Artool

Discovery

Data Base

AnalysisPre-processing

DB

Output Data

Pattern AnalysisPattern Discovery

Input Data Conventional and semantic

Preprocessing

Web Analyst

Input AdapterAccess Logs

Knowledge Base

Input AdapterAccess Log Adapter

SemanticPreprocessor

Preprocessor

Data Condensing

SystemMetrics Tool

SelectedUsage Mining Algorithms Association Rules Sequentional Patterns

Adaptation Rules

Sequential Rules: Algorithm: SPAM Tool: Himalaya Data Mining

Tools

New item problem Recommendation of new

items C1 & C2 C3


Rule Design

Run-timeDesign-time

RuleDesign

Portal Annotation



Adaptation Rules

Modeling Cycle


Ontology Transformer

Transformation of all of parts into a client-readable format that can be executed by a browser's JavaScript engine

Ontologies and rules must be translated beforehand in easy-to-parse and effortlessly executable format

Materialization of all ontologies at the server by using an off-the-shelf OWL reasoner Consistency checks and derivation of the class hierarchy

Run-timeDesign-time

RuleDesign

Portal Annotation



Adaptation Rules

Modeling Cycle


OWL / SWRL To JSON Transformer

PortalEntity

Element

ActiveElement

Button (1)

ResetButton

SubmitButton

var Button = { "indi" : [ { "name" : "Button1", "Button1" : { "hasID" : ["btn_1"], "thisclass" : "Button" }}

], "superclass" : "ActiveElement", "subclass" : ["ResetButton", "SubmitButton"]

};

superclass = ActiveElementsubclass = [ResetButton, SubmitButton]hasID = btn_1thisclass = Button

Button1 : Button

Ontology Transformator (Design-time)

Object Builder (Run-time)

Protégé

JSON

XMLHttpRequest

eval()

Ontology-JSON Converter (Adaption Model Ontology)

<swrl:Imp rdf:ID="Rule-1"> <swrl:body> ECMAEvent(?a) type(?a, “click“) </swrl:body> <swrl:head> Click(?a) </swrl:head></swrl:Imp>

ECMAEvent(?a) ^ type(?a, "click") -> Click(?a)

[ { "rdf:ID":"Rule-1", "swrl:body" : { ECMAEvent(?a) type(?a, “click“) }, "swrl:head" : { Click(?a) } }]

SWRL

RDF/XML

JSONStringPart 2

Object Builder

Rule1Rule1Rule1

RulesObject

XMLHttpRequest

eval()


The Transfer Cycle

Run-timeDesign-time

RuleDesign

Portal Annotation



User Model Transfer

Ontology Transfer

Adaptation Rules

Modeling Cycle

Transfer Cycle


The Adaptation Cycle

Run-timeDesign-time

RuleExecution

UserTracking

PortalAdaptation

RuleEvaluation

User Model

RuleDesign

Portal Annotation



User Model Transfer

Ontology Transfer

Adaptation Rules

Modeling Cycle Adaptation Cycle

Transfer Cycle


Run-time Architecture

Internal BrowserRepresentation

JavaScript/JSONPresentation

Event Handler

DOM

UIAdaptation

UserTracking

Manipulate

User Interactions

RuleEngine

User Model

Adaptation Rules

Update

Call

Call

Trigger

Read

Read





Agenda


Evaluation

Proof of concept for the FIT ontologies Less than 500 concepts About 20 rules

Results Initial Client-side concept creation 500 concepts: 20 ms

0500

100015002000250030003500

Time (ms)

100 10000 50000

Concepts

Rule execution time 20 rules: 78 ms

0

500

1000

1500

2000

Time (ms)

10 20 50 100 200 500

Number of Rules

Intel Pentium 1,6 GHz, 2 GB RAM, Windows XP, Internet Explorer 6, Firefox 2


Evaluation cont’d

T-Box expressions shrank to a simple taxonomy Subsumption hierarchy without:

OWL class axioms (equivalent class) Class descriptions (union of) Information about relations are completely lost

Individuals are transformed without information loss

Complexity problems with the sequential algorithm


Conclusions

Prototypical implementation of an responsive RIA based on declarative rules and ontologies.

Discussion Annotation of RIAs extremely difficult, time-consuming and error-prone Even more the maintenance of the annotations Semantic datamining results did not meet the expectations Due to exponential run-time behavior more sophisticated algorithms needed SWRL not sufficient for expressing temporal logic constructs: ECA rules needed


Questions?

Thank you!

SYSTEMATIC THOUGHT LEADERSHIP FOR INNOVATIVE BUSINESS A User Interface Adaptation Architecture for Rich Internet Applications ESWC 2008 Kay-Uwe Schmidt,

Documents

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