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My Research and e-Business Virendrakumar C. Bhavsar Professor and Director, Advanced Computational Research Laboratory Faculty of Computer Science University.

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Presentation on theme: "My Research and e-Business Virendrakumar C. Bhavsar Professor and Director, Advanced Computational Research Laboratory Faculty of Computer Science University."— Presentation transcript:

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

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 Café Cosine Measure method: Café Cosine 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 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 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, 3 rd 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, …


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