Vagan%20Terziyan

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Intelligent Web Applications (Part 1)Course
Introduction
Vrije Universiteit Amsterdam, Fall 2002

• Vagan Terziyan
• AI Department, Kharkov National University of
  Radioelectronics /
• MIT Department, University of Jyvaskyla
• vagan_at_it.jyu.fi terziyan_at_yahoo.com
• http//www.cs.jyu.fi/ai/vagan/index.html
• 358 14 260-4618

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Contents

• Course Introduction
• Lectures and Links
• Course Assignment
• Examples of course-related research

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Course (Part 1) FormulaWeb Personalization
Web Mining Semantic Web Intelligent Agents
Intelligent Web Applications
- Why ? - To be able to intelligently utilise
huge, rich and shared web resources and services
taking into account heterogeneity of sources,
user preferences and mobility.
- What included ? - Introduction to Web content
management. Web content personalization.
Filtering Web content. Data and Web mining
methods. Multidatabase mining. Metamodels for
knowledge management. E-services and their
management in wired and wireless Internet.
Intelligent e-commerce applications and mobility
of users. Information integration of
heterogeneous resources.
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Practical Information

• 9 Lectures (2 x 45 minutes each, in English)
  during period 28 October - 15 November according
  to the schedule
• Course slides available online plus hardcopies
• Practical Assignment (make PowerPoint
  presentation based on a research paper and send
  electronically to the lecturer until 10
  December)
• Exam - there will be no exam. Evaluation mark for
  this part of the course will be given based on
  the Practical Assignment

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IntroductionSemantic Web - new Possibilities
for Intelligent web Applications
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Motivation for Semantic Web
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Semantic Web Content New Users
applications
agents
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Some Professions around Semantic Web
AI Professionals
Content creators
Content
Logic, Proof and Trust
Mobile Computing Professionals
Web designers
Ontologies
Agents
Annotations
Ontology engineers
Software engineers
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Semantic Web Resource Integration
Semantic annotation
Shared ontology
Web resources / services / DBs / etc.
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What else Can be Annotated for Semantic Web ?
External world resources
Web resources / services / DBs / etc.
Web users (profiles, preferences)
Shared ontology
Web agents / applications
Web access devices
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Word-Wide Correlated Activities
Semantic Web
Agentcities is a global, collaborative effort to
construct an open network of on-line systems
hosting diverse agent based services.
Semantic Web is an extension of the current web
in which information is given well-defined meaning
, better enabling computers and people to work
in cooperation
Agentcities
Grid Computing
Wide-area distributed computing, or "grid
technologies, provide the foundation to a number
of large-scale efforts utilizing the global
Internet to build distributed computing and
communications infrastructures.
FIPA
FIPA is a non-profit organisation aimed at
producing standards for the interoperation of
heterogeneous software agents.
Web Services
WWW is more and more used for application to
application communication. The programmatic
interfaces made available are referred to as Web
services. The goal of the Web Services Activity
is to develop a set of technologies in order to
bring Web services to their full potential
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University of Jyvaskyla ExperienceExamples of
Related Courses
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IWA Course (Part 1) Lectures
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Lecture 1 Web Content Personalization Overview
http//www.cs.jyu.fi/ai/vagan/Personalization.ppt
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Lecture 2 Collaborative Filtering
http//www.cs.jyu.fi/ai/vagan/Collaborative_Filter
ing.ppt
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Lecture 3 Dynamic Integration of Virtual
Predictors
http//www.cs.jyu.fi/ai/vagan/Virtual_Predictors.p
pt
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Lecture 4 Introduction to Bayesian Networks
http//www.cs.jyu.fi/ai/vagan/Bayes_Nets.ppt
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Lecture 5 Web Mining
http//www.cs.jyu.fi/ai/vagan/Web_Mining.ppt
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Lecture 6 Multidatabase Mining
http//www.cs.jyu.fi/ai/vagan/MDB_Mining.ppt
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Lecture 7 Metamodels for Managing Knowledge
http//www.cs.jyu.fi/ai/vagan/Metamodels.ppt
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Lecture 8 Knowledge Management
http//www.cs.jyu.fi/ai/vagan/Knowledge_Management
.ppt
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Lecture 9 E-Services in Semantic Web
http//www.cs.jyu.fi/ai/vagan/E-Services.ppt
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IWA Course (Part 1) Practical Assignment
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Practical assignment in brief

• Students are expected to select one of below
  recommended papers, which is not already selected
  by some other student, register his/her choice
  from the Course Assistant and make PowerPoint
  presentation based on that paper. The
  presentation should provide evidence that a
  student has got the main ideas of the paper, is
  able to provide his personal additional
  conclusions and critics to the approaches used.

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Evaluation criteria for practical assignment

• Content and Completeness
• Clearness and Simplicity
• Discovered Connections to IWA Course Material
• Originality, Personal Conclusions and Critics
• Design Quality.

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Format, Submission and Deadlines

• Format PowerPoint ppt. (winzip encoding
  allowed), name of file is students family name
• Presentation should contain all references to the
  materials used, including the original paper
• Deadline - 10 December 2002
• Files with presentations should be sent by e-mail
  to Vagan Terziyan (terziyan_at_yahoo.com AND
  vagan_at_it.jyu.fi)
• Notification of evaluation - until 15 December.

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Papers for Practical Assignment (1)

• Paper 1 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_1_P.pdf
• Paper 2 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_2_P.pdf
• Paper 3 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_3_CF.ps
• Paper 4 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_4_CF.pdf
• Paper 5 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_5_MW.pdf
• Paper 6 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_6_BN.ps
• Paper 7 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_7_BN.pdf
• Paper 8 http//www.cs.jyu.fi/ai/vagan/course_pape
  rs/Paper_8_MM.pdf

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Papers for Practical Assignment (2)

• Paper 9 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_9_WM.ps
• Paper 10 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_10_WM.pdf
• Paper 11 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_11_III.pdf
• Paper 12 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_12_III.pdf
• Paper 13 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_13_KM.pdf
• Paper 14 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_14_ES.pdf
• Paper 15 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_15_MDB.pdf
• Paper 16 http//www.cs.jyu.fi/ai/vagan/course_pap
  ers/Paper_16_MDB.pdf

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University of Jyvaskyla Experience Examples of
Course-Related Research
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Mobile Location-Based Service in Semantic Web
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Mobile Transactions Management in Semantic Web
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P-Commerce in Semantic Web
Terziyan V., Architecture for Mobile P-Commerce
Multilevel Profiling Framework, IJCAI-2001
International Workshop on "E-Business and the
Intelligent Web", Seattle, USA, 5 August 2001, 12
pp.
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Semantic Metanetwork for Metadata Management
Semantic Metanetwork is considered formally as
the set of semantic networks, which are put on
each other in such a way that links of every
previous semantic network are in the same time
nodes of the next network. In a Semantic
Metanetwork every higher level controls semantic
structure of the lower level.
Terziyan V., Puuronen S., Reasoning with
Multilevel Contexts in Semantic Metanetworks, In
P. Bonzon, M. Cavalcanti, R. Nossun (Eds.),
Formal Aspects in Context, Kluwer Academic
Publishers, 2000, pp. 107-126.
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Petri Metanetwork for Management Dynamics

• A metapetrinet is able not only to change the
  marking of a petrinet but also to reconfigure
  dynamically its structure
• Each level of the new structure is an ordinary
  petrinet of some traditional type.
• A basic level petrinet simulates the process of
  some application.
• The second level, i.e. the metapetrinet, is used
  to simulate and help controlling the
  configuration change at the basic level.

Terziyan V., Savolainen V., Metapetrinets for
Controlling Complex and Dynamic Processes,
International Journal of Information and
Management Sciences, V. 10, No. 1, March 1999,
pp.13-32.
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Bayesian Metanetwork for Management Uncertainty
Terziyan V., Vitko O., Bayesian Metanetworks for
Mobile Web Content Personalization, In
Proceedings of 2nd WSEAS International Conference
on Automation and Integration (ICAI02), Puerto
De La Cruz, Tenerife, December 2002.
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Multidatabase Mining based on Metadata
Puuronen S., Terziyan V., Logvinovsky A., Mining
Several Data Bases with an Ensemble of
Classifiers, In T. Bench-Capon, G. Soda and M.
Tjoa (Eds.), Database and Expert Systems
Applications, Lecture Notes in Computer Science,
Springer-Verlag, V. 1677, 1999, pp. 882-891.