My Research and e-Business Virendrakumar C. Bhavsar Professor and Director, Advanced Computational Research Laboratory F

1. My Research and e-Business Virendrakumar C. Bhavsar Professor and Director, Advanced Computational Research Laboratory Faculty of Computer Science University of New Brunswick Fredericton, NB bhavsar@unb.ca www.cs.unb.ca/profs/bhavsar www.cs.unb.ca/acrl

2. Outline • Past Research Work • Current Research Work • Future Research Work • Conclusion

3. Past Research Work • Parallel/Distributed Processing • - Parallel Computer Architecture • Design and Analysis of Parallel Algorithms • Real-time and Fault-Tolerant Systems • Artificial Neural Networks • Learning Machines and Evolutionary • Computation •  Computer Graphics • Visualization

4. Past Research Work (cont.) • Multimedia for Education: Intelligent Tutoring Systems • Multi-Lingual Systems and Transliteration • Web Portal for an NB company • Clustifier and Extractor (IIT, NRC, Ottawa) • Intelligent User Profile Generator • Multi-Agent Systems • with Dr. Marsh (IIT, NRC, Ottawa) •  Supervision/Co-supervision • 50 master's theses; 4 doctoral theses • 5 post-doctoral fellows/research associates

5. Current Research Work (cont.) • Parallel/Distributed Processing • - C3-Grid development • - Design and analysis of parallel/distributed • applications • Multi-Agent Systems • - Specification and verification of multi-agent systems • with Dr. Mironov, Russia • Information Sharing in Multi-agent Systems • with Dr. Ghorbani, UNB

6. ACORN • Information diffusion and search in networks • All pieces of information - Agents - documents; images, etc. • Applications B2B and B2C e-Commerce solutions Virtual community creation and support systems Personalized directed information handling

7. ACORN: Relation to Other Work • Search Engines e.g. Alta Vista, Excite, Yahoo, InfoSeek, and Lycos If the user has to search, it’s because the information diffusion is • not fast enough • not accurate enough • Recommender Systems • Firefly (Maes), Fab (Balabanovic) • Content-based or Collaborative • ACORN’s agents: a mixture of both Matchmakers • Yenta (Foner) • Very close to the ACORN spirit; lacks the flexibility of ACORN

8. ACORN: Relation to Other Work (cont.) • Web Page Watchers and Push Technologies • Tierra, Marimba, Channels • ACORN is a means of pushing new data, reducing the need to watch for changes • Filtering Systems • The filtering in ACORN is implicit in what is recommended by humans • ‘Knowbots’ • Softbots (Washington, Etzioni, Weld), Nobots (Stanford, Shoham) • mobile agents for internet search • ACORN provides diffusion also

9. S e r v e r Café S e r v e r S e r v e r S e r v e r Café Café tom@ucsd.edu ucsd.edu ymasrour@ai.it.nrc.ca ai.it.nrc.ca S e r v e r bob@ai.it.nrc.ca dick@ucsd.edu steve@ai.it.nrc.ca anwhere.else foo@anywhere.else cs.stir.ac.uk meto.gov.uk joan@unb.ca Clients bhavsar@unb.ca wibble@cs.stir.ac.uk graham@cs.stir.ac.uk anne@cs.stir.ac.uk

10. Café • At set intervals, agents present are compared, and relevant information exchanged • Keyphrase-based Information Sharing • A unique method of automating community based information sharing

11. CaféCosine Measure method: Similarity of Article 3 (Category 1)

12. Performance Evaluation of ACORN • Test-bed: Several Autonomous Servers, each serving autonomous virtual users • Virtual User - capable of creating agents - picks up a topic from a client core’s interest - migrates to other servers - potential destinations

13. Performance Evaluation of ACORN

14. Future Research Work Multi-Agent Systems: B2B-B2C Extensions User-driven personalization • Personalized and personalizable automatic delivery and search for information • Directed advertisements based on user profiles and preferences • agent learning • Data mining over large distributed networks and databases Automated and manually-driven user profile generation and update

15. Future Research Work (cont.) Multi-Agent Systems for Distributed Databases- continuous updating of large and distributed databases on intranets and the Internet Multi-Agent Systems - Very naturally satisfy many requirements in such an environment - Provide a very flexible and open architecture - Scalability analysis with multiprocessor servers

16. Professional Activities • Professional Involvement - Chair, IEEE NB Section - The C3.ca Association, Inc.(the Canadian Consortium for High Performance Computing) Member, Executive Committee and BoD • Organized many workshops and conferences - Program-Co-Chair, HPCS’2002, June 17-19, 2002, Moncton, NB - Technical Committee Member, 3rd Workshop on Parallel Distributed Science and Engineering Computing with Applications, Fort Lauderdale, FL, April 15-19, 2002. - Program Committee Member, Grid Canada, Toronto, February, 2002.

17. Conclusion • Broad research background • Collaborations - IIT, NRC, Ottawa - UNB, Univ. of IL, USC, C-DAC India, and other institutions • Professional Involvement • e-Business related interests - e.g. user profiling, multi-agent systems, Learning and e-Learning, multi-lingual web, high performance web servers, …