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Call for Papers
Microsoft Word version of this document
PDF versionThe First Announcement and Call for Papers
AIS-ADM-07: The International Workshop on Autonomous Intelligent Systems: Agents and Data Mining
June 3-5, 2007, St. Petersburg, Russia
http://space.iias.spb.su/ais07
Sponsors:
1. St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS)
2. St. Petersburg Scientific Center of the Russian Academy of Sciences
3. Binghamton University (State University of New York)
1. Title and scope: "Autonomous Intelligent Systems: Agents and Data Mining"
Since early 1990, multi-agent systems (MAS) and data mining and knowledge discovery (KDD) have remained areas of high interest for the research and development in intelligent information technologies. The multi-agent system technology offered powerful metaphors for information system conceptualization, a range of new architectures, techniques, and technologies specifically focused on the design and implementation of large-scale distributed intelligent systems operating in open heterogeneous environment. This technology is now approaching its industrial maturity, thus helping to cope with design, implementation, and deployment of critical industrial applications in many domains.
KDD technology also provides intelligent information technology with powerful ideas, algorithms, and software means intended for answering the main question of many Artificial Intelligence applied problems, "Where does the knowledge come from?", thus actually making modern applications intelligent and adaptive.
The evident recent trend in both science and industry is to integrate these technologies in order to use advantages of them both. The existing experience with combined application of multi-agent technology to design architectures of distributed data mining and KDD systems, and the utilization of distributed data mining and KDD to support learning tasks in multi-agent research, confirms the fact that both technologies are capable of mutual enrichment and their joint use results in information systems with emergent properties.
For instance, MAS architectures are used for distributed data mining and knowledge discovery systems, particularly, for distributed learning in data fusion systems making decisions based on many distributed heterogeneous data and information sources. The use of multi-agent technology in very large-scale data mining and KDD tasks is another example of the same trend. In return, multi-agent systems utilize data mining and KDD as a source of innovative ideas to provide applications more intelligence and adaptability.
The emergent technology may be outlined by such key words as autonomous intelligence, distributed intelligence, learning intelligence, emergent intelligence, emergent intelligent behavior, etc. It is worth noting that a number of very specific research problems arise on the cross-boundary of multi-agent, data mining and KDD technologies. The examples are specification framework and representation structures for distributed intelligence, the new role of ontology, joint use of knowledge extracted from different heterogeneous sources, protocols for distributed data mining, etc. Rapidly developing intelligent agent-based ad-hoc networks technology in particular, operating on peer-to-peer basis, represents one more example of the topmost problems currently given increasing attention from the scientific and industrial communities. Ubiquitous computing and ubiquitous knowledge discovery forming a class of novel distributed intelligent technology is practically infeasible without integration of multi-agent and KDD technologies.
During the past years, interest in joint use of the multi-agent and KDD technologies has also been proven by several successful international conferences and workshops which were devoted to the problem in question, either fully or partially.
The success of the First International Workshop "Autonomous Intelligent Systems: Agents and Data Mining" (AIS-ADM-05) held in June 2005 in St. Petersburg, Russia (http://space.iias.spb.su/ais05, LNAI-3505) confirmed the world wide interest in the theoretical and applied aspects of the new technology integrating agents, data mining and knowledge discovery.
However, like any newly emergent technology, integration of multi agent and data mining and KDD within distributed intelligent systems brought forward a number of novel problems and challenges. The Second International Workshop "Autonomous Intelligent Systems: Agents and Data Mining" (AIS-ADM-07) that will be held from June 3-5, 2007, in St. Petersburg, Russia, is intended for discovery and analysis of the aforementioned problems and challenges, as well as for sharing of new ideas, scientific results, lessons learned, and the best practices within the new cross boundary area integrating multi-agent and data mining and KDD technologies.
The Workshop invites researchers from both academia and industry to jointly discuss various aspects of theory and applications, as well as new opportunities provided by integration and interaction of multi-agent and data mining and KDD.
The list of main topics of the Workshop include but are not limited to:
- Intelligent agents for Data Mining and KDD
- Agent-based architectures for distributed data mining and KDD
- Agent-based infrastructure for distributed data mining and KDD
- Agent-based coordination of distributed data mining and KDD
- Agent-based peer-to-peer distributed data mining and KDD
- Agent technology for ubiquitous data mining
- Knowledge discovery via mobile agents in ubiquitous environments
- Agent security in ubiquitous environments
- Mobile agents in sensor networks: challenges, solutions, scalability.
- Protocols for agent-based distributed data mining and KDD
- Protocols for agent-based ubiquitous data mining and KDD
- Ontologies for agent-based distributed data mining and KDD
- Agent-based software tools for data mining and KDD
- Agent technology in collaborative Web filtering
- Agent-based context sensitive web mining and global information foraging
- Ontology-based web mining
- Agent-based meta-knowledge discovery and representation
- Adaptation and Learning in multi-agent systems
- Evolution and Individual Learning in Multi-Agent Systems
- Distributed Learning of agents of multi-agent systems
- Distributed Learning of protocol selection in cooperative multi-agent systems
- Learning of Coordination in multi-agent systems
- Challenges associated with integration of agent and data mining
- Lessons learned
- Surveys and case studies
- Applications (intrusion detection, situational awareness, learning of situation assessment, emergency monitoring and response, agent-based data and information fusion, etc.)
- Surveys on integration of agent and data mining and KDD technologies
| Inclusive dates of Workshop: | ||
| June 2-6, 2007, (arrival on June 2, technical program June 3-5, departure on June 6) | ||
| For submission | ||
| Paper drafts: | January 10, 2007 | |
| Acceptance notification: | February 5, 2007 | |
| Camera ready papers due | March 4, 2007 | |
| For registration | ||
| Early registration deadline: | before April 20, 2007 | |
| On site registration: | June 2-5, 2007 | |
| Hotel reservation request: | May 10, 2007 | |
3. Paper submission
The Workshop welcomes original, not previously published, papers from academic, government, and industry contributors on the above proposed and closed topics. All submissions will be subjected to a thorough review by at least two reviewers. Draft versions of original full papers up to 5500 words in English, including abstract (up to 300 words) and keywords (3 to 5), should be submitted by January 10, 2007 or sooner via upload through the Workshop web site at http://space.iias.spb.su/ais07. Only electronic submissions in PostScript or PDF formats will be accepted.
Guidelines for the proceedings camera-ready manuscripts of the accepted papers
Proceedings of the Workshop will be published by Springer Verlag Publishers in "Lecture Notes in Computer Science" series.
www.springer.com/lncs That is why camera-ready manuscripts of the accepted
papers should be formatted in accordance with Springer Verlag Publishers
requirements (in MS Word or LATEX formats). When preparing your paper,
please follow the guidance from the Information for Authors.
The authors of accepted papers must strictly follow the aforementioned
rules and templates. Camera ready paper submission can be made via e-mail
ais@mail.iias.spb.su and also uploaded through the Workshop web site at
http://space.iias.spb.su/ais07/
The working language of the Workshop is English. The papers and presentation materials must be in English.
5. Workshop Website
All materials concerning AIS-ADM-07 preparation, program, and other arrangements can be found at the regularly updated web site http://space.iias.spb.su/ais07.
6. The Principal Invited Speakers
1 Hillol Kargupta
Associate Professor in the Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County
Peer-to-Peer Data Mining: Local Algorithms, Privacy Issues, and Games (abstract)
2 Ning Zhong
Head of Knowledge Information Systems Laboratory, and Professor in Department of Life Science and Informatics at Maebashi Institute of Technology, Japan, and Director and Adjunct Professor in the International WIC Institute, Beijing University of Technology, China
WI Based Multi-Aspect Data Analysis in a Brain Informatics Portal (abstract)
3 Sandip Sen
Professor of Computer Science in the University of Tulsa
Robust Agent Communities (abstract)
4 Vladimir F. Khoroshevsky
Head of Applied Intelligent Systems Division in Computer Centre Russian Academy of Sciences, Moscow; Ontos AG Chief Scientist
Ontos Solutions for Semantic Web: Text Mining, Navigation and Analytics (abstract)
Hillol Kargupta
Associate Professor in the Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County
Peer-to-Peer Data Mining: Local Algorithms, Privacy Issues, and Games
Abstract. Peer-to-Peer (P2P) networks are gaining increasing popularity in many distributed applications such as file-sharing, network storage, web caching, searching and indexing of relevant documents and P2P network-threat analysis. Many of these applications require scalable analysis of data over a P2P network. This talk will focus on P2P distributed data stream mining and monitoring. It will first discuss the foundation of local P2P algorithms for data analysis and present some examples. Next it will discuss some of the privacy concerns with P2P data mining and point out the problems of existing privacy-preserving multi-party data mining techniques which usually assume that the parties abide by the protocols as expected, compute whatever is needed, communicate correctly following the rules, and do not collude with other parties for exposing third party sensitive data. Rest of the talk will argue that most of these nice assumptions fall apart in real-life applications of privacy-preserving distributed data mining (PPDM). The talk will offer a more realistic formulation of the PPDM problem as a multi-party game where each party tries to maximize its own objective or utility. The talk will develop a game-theoretic framework and discuss some recent results. It will also discuss equilibrium-analysis of such games and describe some local distributed algorithms that are based on such game theoretic frameworks.
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Hillol Kargupta is an Associate Professor in the Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County. He received the PhD degree in computer science from the University of Illinois at Urbana-Champaign in 1996. He is also a co-founder of Agnik LLC, a data analytics company for distributed, mobile, and embedded environments. His research interests include mobile and distributed data mining and computation in biological process of gene expression. Dr. Kargupta won a US National Science Foundation CAREER award in 2001 for his research on ubiquitous and distributed data mining. He along with his coauthors received the best paper award at the 2003 IEEE International Conference on Data Mining for a paper on privacy-preserving data mining. He won the 2000 TRW Foundation Award and the 1997 Los Alamos Award for Outstanding Technical Achievement. His research has been funded by the US National Science Foundation, US Air Force, Department of Homeland Security, NASA, and various other organizations. He has published more than 80 peer-reviewed articles in journals, conferences, and books. He has co-edited two books: Advances in Distributed and Parallel Knowledge Discovery, AAAI/MIT Press, and Data Mining: Next Generation Challenges and Future Directions, AAAI/MIT Press. He is an associate editor of the IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Systems, Man, and Cybernetics, Part B and Statistical Analysis and Data Mining Journal. He was the program-co-chair of the 2005 SIAM Data Mining Conference, Program vice-chair of 2005 PKDD Conference, Program vice-chair of 2005 IEEE International Data Mining Conference, Program Vice Chair for 2005 Euro-PAR Conference, Associate General Chair of the 2003 ACM SIGKDD Conference, and chair of the 2002 NSF Next Generation Data Mining Workshop among others. He regularly serves in the organizing and program committee of many data mining conferences. More information about him can be found at http://www.cs.umbc.edu/~hillol. |
Ning Zhong
Head of Knowledge Information Systems Laboratory, and Professor in Department of Life Science and Informatics at Maebashi Institute of Technology, Japan, and Director and Adjunct Professor in the International WIC Institute, Beijing University of Technology, China
WI Based Multi-Aspect Data Analysis in a Brain Informatics Portal
Abstract. In order to investigate human information processing mechanism systematically, Web intelligence (WI) based portal techniques are required for brain data measurement, management and analysis. Building a brain informatics portal is, in fact, to develop a data mining grid centric multi-layer grid system, on which various data mining agents are deployed, for multi-aspect data analysis. We propose an approach for collecting, modeling, transforming, managing, and mining multiple human brain data obtained from systematic fMRI/EEG experiments. The proposed approach provides a new way in Brain Informatics for automatic analysis and understanding of human brain data to replace human-expert centric visualization. We attempt to change the perspective of cognitive scientists from a single type of experimental data analysis towards a holistic view at a long-term, global field of vision to understand the principle, models and mechanisms of human information processing.
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Ning Zhong received the Ph.D. degree in the Interdisciplinary Course on Advanced Science and Technology from the University of Tokyo. He is currently head of Knowledge Information Systems Laboratory, and a professor in Department of Systems and Information Engineering at Maebashi Institute of Technology, Japan. He is also director and an adjunct professor in the International WIC Institute (WICI), Beijing University of Technology. He has conducted research in the areas of knowledge discovery and data mining, rough sets and granular-soft computing, Web intelligence, intelligent agents, brain informatics, and knowledge information systems, with over 150 journal and conference publications and 10 books. He is the editor-in-chief of the Web Intelligence and Agent Systems journal (IOS Press), and Annual Review of Intelligent Informatics (World Scientific), associate editor of IEEE Transactions on Knowledge and Data Engineering, and the Knowledge and Information Systems journal (Springer), a member of the editorial board of Transactions on Rough Sets (Springer), and the editorial board of Advanced Information and Knowledge Processing (AI&KP) book series (Springer), Frontiers in AI and Applications book series (IOS Press), and editor (the area of intelligent systems) of the Encyclopedia of Computer Science and Engineering (Wiley). He is the co-chair of Web Intelligence Consortium (WIC), chair of the IEEE Computer Society Technical Committee on Intelligent Informatics (TCII), member of the steering committee of IEEE International Conferences on Data Mining (ICDM), IEEE GrC Task Force Committee and the Advisory Board, the steering committee of International Rough Set Society. He has served or is currently serving on the program committees of over 80 international conferences and workshops, including IEEE ICDM'02 (conference chair), IEEE ICDM'06 (program chair), IEEE/WIC WI-IAT'03 (conference chair), IEEE/WIC/ACM WI-IAT'04 (program chair), and IJCAI'03 (advisory committee member). He is a senior member of IEEE, and a member of IPSJ, JSAI, IEEE-CS, IEEE-SMC, ACM, AAAI, and IRSS. |
Sandip Sen
Professor of Computer Science in the University of Tulsa
Robust Agent Communities
Abstract. We believe that intelligent information agents will represent their users interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services. Such information worlds will present unforeseen opportunities as well as challenges that can be best addressed by robust, self-sustaining agent communities. An agent community is a stable, adaptive group of self-interested agents that share common resources and must coordinate their efforts to effectively develop, utilize and nurture group resources and organization. More specifically, agents will need mechanisms to benefit from complementary expertise in the group, pool together resources to meet new demands and exploit transient opportunities, negotiate fair settlements, develop norms to facilitate coordination, exchange help and transfer knowledge between peers, secure the community against intruders, and learn to collaborate effectively. In this talk, I will summarize some of our research results on trust-based computing, negotiation, and learning that will enable intelligent agents to develop and sustain robust, adaptive, and successful agent communities.
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Sandip Sen is a Professor of Computer Science in the University of Tulsa with primary research interests in multiagent systems, machine learning, and evolutionary computation. He completed his PhD in the area of intelligent, distributed scheduling from the University of Michigan in December, 1993. He has authored approximately 2000 papers in workshops, conferences, and journals in several areas of artificial intelligence. In 1997 he received the prestigious CAREER award given to outstanding young faculty by the National Science Foundation. He has served on the program committees of most major national and international conferences in the field of intelligent agents. He has chaired multiple international workshops and symposia on agent learning and reasoning. He has also presented several tutorials on multiagent systems in association with the leading international conferences on autonomous agents and multiagent systems. |
Vladimir F. Khoroshevsky
Head of Applied Intelligent Systems Division in Computer Centre Russian Academy of Sciences, Moscow; Ontos AG Chief Scientist
Ontos Solutions for Semantic Web: Text Mining, Navigation and Analytics
Abstract. The talk will discuss the problem of development and implementation of semantic navigation through Web-content. Multi-agent architecture of a solution for Semantic Web and innovative services are presented. In the context of the proposed solution Web mining is carried out by special OntosMiner agents, which provide the ontology-driven processing of multilingual text collections on the basis of the special kind of content extraction technologies. First evaluation results of the presented solution are discussed as well.
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DrSc., Prof. Vladimir Khoroshevsky has worked extensively in the fields of software engineering, artificial intelligence and natural language processing. He has more than 120 publications in domains, in particularly, in Knowledge-Based Software Engineering, Knowledge Representation, Multi-Agent Systems, Natural Language Processing, Information and Content Extraction, Ontology Engineering, etc., author of 3 monographs published by known Russian Publishers "Radio and Svyaz" and "Piter Press". He is also Corresponding Member of Russian Academy of Natural Sciences, Member of the Board of Russian Association of Artificial Intelligence (RAAI), Board Member of RAAI Scientific Journal "AI News", member of Program Committees of different International Conferences, in particularly, CAI '88-'06, AIMSA '98-'02, JCKBSE '96-'06, RANLP '2003, etc.
Main Research Interests: Artificial Intelligence Software, Knowledge Based Software Engineering; Expert Systems and Tools; Multi Agent Systems; Applied Semiotics, Semantic Web; Natural Language Processing, Information and Content Extraction; Knowledge Management, Ontology Engineering. |
Sponsors:
TBC
Information about sponsors will be posted on the Workshop web site.
Organizers:
Information about organizers will be posted at the Workshop web site.
Chairmen:
Prof. R.M. Yusupov, Director of the St. Petersburg Institute
Prof. Victor Skormin, Binghamton University, AFRL/IF, USA
Local contact person Irina Podnozova
Phone: +7-(812)-328-4446 Fax: +7-(812)-328-0685
E-mail: ipp@mail.iias.spb.su
Local Organizing Committee
Chairman
R.M. Yusupov, Director of the St. Petersburg Institute for Informatics and Automation (SPIIRAS)
Organizing Committee members:
1. I.Podnozova, (SPIIRAS, St. Petersburg)
2. A.Tkatch (SPIIRAS, St. Petersburg, Vice Chairman)
3. D.Bakuradze (SPIIRAS, St. Petersburg)
4. O.Karsaev (SPIIRAS, St. Petersburg)
5. V.Samoilov (SPIIRAS, St. Petersburg)
6. V.Konushy (SPIIRAS, St. Petersburg)
7. E.Mankov (SPIIRAS, St. Petersburg)
8. A.Malyshev (SPIIRAS, St. Petersburg)
9. S.Serebrykov (SPIIRAS, St. Petersburg)
10. V.Tikhomirov (SPIIRAS, St. Petersburg)
11. D.Trotskiy (SPIIRAS, St. Petersburg)
8. Program Committee
Chairmen:
Vladimir Gorodetsky (SPIIRAS, Russia, http://space.iias.spb.su/ai/gorodetski/gorodetski.jsp)
Chengqi Zhang (Sydney University of Technology, Australia, http://www.staff.it.uts.edu.au/~chengqi/)
Victor Skormin (Binghamton University, USA, http://www.ee.binghamton.edu/lasercom/vskormin/)
Longbing Cao (University of Technology, Sydney, Australia, http://www-staff.it.uts.edu.au/~lbcao/)
Program Committee members:
Shlomo Berkovsky (University of Haifa, Israel)
Sviatoslav Braynov (University of Illinois, USA)
Cory Butz (University of Regina, Canada)
Wei Dai (Victoria University, Australia)
Nathan Griffiths (University of Warwick, UK)
Heikki Helin (TeliaSonera, Finland)
Henry Hexmoor (South. Illinois University, USA)
Xiaohua (Tony) Hu (Drexel University, Philadelphia, USA)
Seunghyun Im (Univ. of Pittsburgh at Johnstown, USA)
Xiaolong Jin (University of Bradford, UK)
Oleg Karsaev (SPIIRAS, Russia)
Kristian Kersting (University of Freiburg, Germany)
Vladimir Khoroshevsky( Computer Center of the Russian Academy of Sciences, Russia)
Matthias Klusch (DFKI, Germany)
Daniel Kudenko (University of York, UK)
Mikko Laukkanen (TeliaSonera, Finland)
Jiming Liu (University of Windsor, Canada)
Michael Luck (University of Southampton, UK)
Simon Miles (University of Southampton, UK)
Vladimir Marik (Czech TU in Prague, Czech Rep.)
Pericles Mitkas (Aristotle University of Thessaloniki, Greece)
Joerg Mueller (Technische University Clausthal, German)
Steve Munroe (University of Southampton, UK)
Mircea Negoita (Pertronic Industries Ltd., New Zealand)
Hung Son Nguyen (Inst. of Decision Support, Poland)
Ngoc Thanh Nguyen (Wroclaw University of Technology, Poland)
Eugenio Oliveira (University of Porto, Portugal)
Leonid Perlovsky (AFRL/IFGA, USA)
Zbigniew Ras (University of North Carolina, USA)
Michele Sebag (CNRS - University Paris-Sud Orsay, France)
Andrzej Skowron (Warsaw University, Poland)
Zhong Zhi Shi (Inst. for Computer Technology, China)
Alexander Smirnov (SPIIRAS, Russia)
Katia Sycara (Carnegie Mellon University, USA)
Andreas Symeonidis (Aristotle University of Thessaloniki, Greece)
Boleslaw Szymanski (Rensselaer Polytech. Institute, USA)
Huaglory Tianfield (Glasgow Caledonian University, UK)
Santtu Toivonen (VTT Tech. Res. Centre, Finland)
Ran Wolff (Haifa University, Israel)
Philipp Yu (IBM Thomas J. Watson Research Center, USA)
Nikolay Zagoruiko (Inst. for Mathematics, Russia)
Yanqing Zhang (Georgia State University, USA)
Wen-Ran Zhang (Georgia Southern University, USA)
Zili Zhang (Deakin University, Australia)
Ning Zhong (Maebashi Inst. of Technology, Japan)
Hai Zhuge (Inst. for Computer Technology, China)
9. Location of the Meeting, Accommodation, Cultural Program
According to the preliminary agreement, the AIS-ADM-07 Workshop will take place in the historical building "Palace of Grand Prince Vladimir Romanov," now "House of Scientists," located in the heart of St. Petersburg, address: 26, Dvortsovaya emb., St. Petersburg, 191186, Russia. This venue allows the conference organizers to arrange for the Workshop itself, as well as for the associated events (informal discussions, reception, breaks, etc.)
All participants are expected to arrive to St. Petersburg directly. Workshop organizers intend to arrange for transportation upon arrival and departure and to/from Workshop venue/other hotel upon a separate request of participants.
The following assistance in housing could be provided by local organizers. We intend to engage a Destination Management Company "Monomax" to assist participants in housing and cultural programs (http://monomax.ru/langeng). It is possible to make reservations at reasonable prices in hotels in the St. Petersburg downtown area from $120 per night (single room), and from $130 per night (double room). Also, reservations in better and more expensive hotels at $150 - $600 per night are available (hotels like Astoria, Europe, Radisson SAS, etc.). For students, the hostel from about $50 may be organized on special request.
10. Visa Issues
All foreign participants of the Workshop should obtain an entry visa to the Russian Federation.
Workshop Service Agency Monomax Meetings & Incentives will provide participants with the visa support papers (invitation & hotel voucher).
Monomax Meetings & Incentives has reference number of the Russian Ministry for Foreign Affairs. Supporting documents will be made based on your personal information submitted on-line at the Visa Support section according to the period of hotel accommodation you have booked.
In order to obtain Russian Tourist Visa please contact the nearest Russian Consulate or Embassy in your home country for the further information.
Monomax Meetings & Incentives will send the visa supporting documents to the participant ONLY after receiving hotel accommodation one night pre-payment!
PLEASE NOTE: In most of cases fax copy of visa support documents is enough. In some countries Russian Consulate requires originals of visa support to be presented. The fee for post courier delivery is charged separately.
The procedure of visa application varies from country to country and could take more than 2 weeks. We recommend you to start it as soon as you know about your participation in the conference.
IMPORTANT GUIDELINES TO FILL OUT YOUR VISA APPLICATION FORM PROPERLY
Purpose of visit: Tourism (please do not state any other purpose of visit).
This will help you to avoid difficulties with your Russian Tourist Visa obtaining, and will help us to shorten and simplify the procedure of invitation letter issue and your registration upon arrival to Saint-Petersburg.
Tourist Visa can not be extended.
Please note that in order to obtain the visa your passport must be valid for at least 3 months after the proposed date.
Migration card
All foreign citizens arriving in Russia have to complete a migration card given at the customs. Please, fill it in carefully and keep safe until you leave the country.
If you have any questions or need our assistance please do not hesitate to contact us at Natalia.Zakharova@monomax.org.
TO ARRANGE INVITATION FOR VISA PLEASE VISIT ONLINE REGISTRATION !
11. Contact us
Program Committee Co-Chairman
Professor Vladimir Gorodetsky
Phone: +7-(812)-323-3570; Fax: +7-(812)-328-0685
E-mail: ais@mail.iias.spb.su
Local contact person
Irina Podnozova
Phone: 7-(812)-328-4446, Fax: +7(812)-328-06-85
E-mail: ipp@mail.iias.spb.su
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