NWeSP 2010 - Plenary Speakers

Plenary 1: Srinivas Padmanabhuni, SETLabs, Infosys, Bangalore, India

Title: "The five frontiers of Web Computing: Social, Cloud, Pervasive and Semantic Perspectives"

Abstract:  The talk will focus on latest trends in extensions of the current form of World Wide Web, as we know it. The talk will cover the following 5 dimensions:
1.      Social Extension to Web
2.      Cloud Architectures
3.      Pervasive Computing
4.      Semantic Web
5.      Immersive and Accessible Web

In these  diverse but increasingly relevant perspectives on evolution of web, the technical perspectives of the relevant challenges in adopting these within enterprise context shall be examined, with a coverage of relevant technologies, information formats and standards involved thereof.  These emergent extensions of web are increasingly shaping tomorrow's enterprise, and consumers alike, and bringing technology closer to our lines. We shall present a  compelling argument for deeper focus, and investigation into the interplay of these separate web evolution trends, via relevant demonstrator use cases, in the process outlining  several accompanying challenges for the research community.

Biography: Dr. Srinivas Padmanabhuni is a Principal Researcher at Software Engineering and Technology Labs (SETLabs), the R and D arm of Infosys Technologies Limited, Bangalore, India. He heads the SOA centre of excellence at SETLabs, Infosys. Dr. Srinivas specializes in Software Engineering aspects related to Global Software Development, Web services, Service Oriented Architecture, Business Process Management, and Cloud computing technologies alongside pursuing interests in semantic web, autonomic computing, intelligent agents, and enterprise architecture. He has been selected for Who's Who in Asia 2007 first edition, in addition to being nominated for Who is Who in the World and Americas 2009 editions. He serves on editorial board of journals and program committees for international conferences in area of web services, SOA, and Software Engineering. He has authored several papers in international conferences including AAAI, ICWS, SCC, GITMA, APSEC,ISEC, and others. He is currently the chairperson of ACM Bangalore chapter. He has served on program committees for several international conferences and workshops including ICWS (International Conference of Web Services), PricAI (Pacific Rim International Conference on AI), NWeSP (International Conference on Next Generation Web Services Practices), Indian Conference on Software Engineering (ICSE) etc. He has given numerous invited speeches at varied industry and academic forums including IEEE and ACM forums, industry CIO seminars like MINDEF CIO Summit, conferences including APSEC, ICWA etc. and architect forums like IASA. He has also authored books and book chapters and articles in some leading professional journals. A book authored by him on Distributed Systems Security, covering SOA security, is due to come out in 2009 by Wiley Press.

Additionally he has filed for multiple patents in the areas of SOA. Prior to Infosys, Dr. Srinivas has worked in multiple capacities in startups out of Canada and USA. Dr. Srinivas holds a doctorate degree in computing science from University of Alberta, Edmonton, Canada. Prior to Ph.D. he secured his B.Tech and M.Tech in computer science from Indian Institutes of Technology at Kanpur and Mumbai respectively.

Plenary 2:  Weisen Guo, The University of Tokyo,  Japan

Title: Matching and Mining in Semantic Graph Data Set Represented by OWL-DL Ontology

Abstract: Semantic Web methods and technologies provide a formal description of concepts, terms, and relationships within a given knowledge domain. The Web Ontology Language (OWL) can be used to describe the knowledge resources within a given knowledge domain. OWL-DL is one of the three OWL sublanguages. Description Logics (DL) are a family of formal knowledge representation languages. A DL knowledge base contains the TBox (terminological box) that describes concept hierarchies and relationships between concepts, and the ABox (assertional box) that states where in the hierarchy individuals belong and the relationships between individuals. Within a given knowledge domain, we can create an OWL-DL ontology as the domain ontology. Using this ontology we can create a description (we called semantic graph) for a knowledge resource, such as a scientific article. For the semantic graphs are computer-understandable, we can do matching and mining on this kind of data in a semantics way.

Semantic matching is the technique to evaluate the semantic similarity of two semantic graphs. Based on the characteristics of the semantic graph data, we presented a matching approach that obtains a matching score between semantic graphs. There dimensions are considered in this approach: matching granularity, similarity scale for instance classes, and logic similarity scale. In order to match two semantic graphs, a five-step method is presented: creation of atomic queries, generalization of queries, addition of rules, evaluation of queries and semantic graphs, and matching score calculation.

Semantic mining is the technique to mine useful patterns from the semantic graph data set. We presented an approach to mine a specific type pattern, relationship associations, from the semantic graph data set. A relationship association is a form of knowledge generalization that is based on binary relationships between instances in semantic graphs. Specifically, relationship associations involve two binary relationships that share a connecting instance and that co-occur frequently in a semantic graph data set. In order to mine relationship associations, a six-step method is presented: generating triple queries, evaluating supports of triple queries, generating relationship association queries, removing duplicate relationship association queries, evaluating supports of relationship association queries, selecting interesting relationship associations.

For the semantic graph data represented by OWL-DL ontology is complex and a new kind of data, there are many open problems need to be solved. Currently, we are studying more reasonable semantic matching methods and more general semantic graph pattern mining algorithms.

Biography: Weisen Guo is a project researcher in the Science Integration Program (Human) in the Department of Frontier Sciences and Science Integration in the Division of Project Coordination at the University of Tokyo. He holds a PhD in Management Science and Technology from the Dalian University of Technology, China. He has served as a lecturer of the Institute of Systems Engineering in the Management School at the Dalian University of Technology, and as an adjunct project manager of the Projects and Results Management Office in the Planning Bureau at the National Natural Science Foundation of China. He has published over 40 refereed papers in various journals and conferences including AEMB, IJKSS, ICDM, ICKM, LBM, ASIST&T, KDIR, CASoN, MLG, JOHO-KANRI, AWIC, ISWC, and KSS. He served as a program committee member at numerous international conferences including ICKM 2009, KSS 2009, MCS 2010, and BIOINFORMATICS 2011. He has received two grants from the National Natural Science Foundation of China and the Liaoning Province Science and Technology Agency of China. His research interests include Semantic Web technology, graph mining, knowledge science and technology, information system engineering.

Plenary 3: Jiří Dvorský and Eliska Ochodkova, VSB - Technical University of Ostrava, Czech Republic

Title: The Statistical Properties of Large Quasigroups

Abstract: With the growing importance of data security a growing effort to find new approaches to the cryptographic algorithms designs appears. One of the trends is to research the use of other algebraic structures than the traditional, such as a quasigroup. Quasigroups are equivalent to the more familiar Latin squares. There are many characteristics that must quasigroups have from the cryptography point of view. They have to be non-commutative, non-associative, non-idempotent and so on. If one want to work with quasigroups of a large order, effective methods of testing their properties are necessary. We present several experiments on various types of guasigroups and their results. We also propose a new classification of quasigroups based upon strings (product elements) obtained by a product of a sequence. Next we propose using of genetic algorithm to evolve quasigroups with good pseudorandom properties.

Biography: Jiří Dvorský received his Ph.D. in Computer Science from Charles University in Prague, Czech Republic, in 2004. His dissertation was on data compression. He is currently senior lecturer at VSB – Technical University of Ostrava where he teaches classes in computer programming. Specific research interests include data compression, artificial neural networks, usage of neural networks in electric power industry. He is currently working on project “Artifical neural network in Geographic Information Systems”.

Plenary 4: Aditya K. Ghose, University of Wollongong, Australia

Title: Business service modeling and analysis: The view through an alternative service-centric lens

Biography: Professor Ghose holds PhD and MSc degrees in Computing Science from the University of Alberta, Canada (he also spent parts of his PhD candidature at the Beckman Institute, University of Illinois at Urbana Champaign and the University of Tokyo) and a Bachelor of Engineering degree in Computer Science and Engineering from Jadavpur University, Kolkata, India. While at the University of Alberta, he received the Jeffrey Sampson Memorial Award. . His research is (or has been) funded by the Australian Research Council, the Canadian Natural Sciences and Engineering Research Council, the Japanese Institute for Advanced Information Technology (AITEC) and various Australian government agencies as well as companies such as Bluescope Steel, CSC, Holocentric and Pillar Administration. His research has been published in the top venues in service-oriented computing (SCC and ICSOC), software modelling (ER), software evolution (IWSSD, IWPSE) and AI (Artificial Intelligence Journal, AAAI, AAMAS and ECAI). He has been an invited speaker at the Schloss Dagstuhl Seminar Series in Germany and the Banff International Research Station in Canada. He has also been a keynote speaker at several conferences, and program/general chair of several others. He is a senior technical advisor to several companies in the areas of constraint programming and business process management, both in Australia and Canada. He reviews for well-regarded journals such as Artificial Intelligence, the IBM Systems Journal and the Journal of Autonomous Agents and Multi-Agent Systems, serves as assessor (Ozreader) for the Australian Research Council and as an external reviewer for the Natural Sciences and Engineering Research Council (NSERC) of Canada and the Science Foundation of Ireland. Professor Ghose is a Research Leader in the Australian Cooperative Research Centre for Smart Services, Co-Director of the Centre for Oncology Informatics at the Illawarra Health and Medical Research Institute, Co-Leader of the University of Wollongong Carbon-Centric Computing Initiative and Co-Convenor of the Australian Computer Society NSW SIG on Green ICT. He is also Vice-President of CORE, Australia's apex body for computing academics.