Symposium on Foundations and Practice of Data Mining 2010
                                Symposium on Cloud Computing and the Web 2010
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Keynote Sessions:

Keynote Sessions will be held in Engineering Auditorium room ENGR 189
Parallel Sessions will be held in rooms ENGR 331, ENGR 338, ENGR 341 and ENGR 343.






8/14 GrC2010 CW2010/12th NFIC 

9:00 AM - 9:30 AM

Opening Session

9:30 AM - 10:30 AM

Dr. Lotfi Zadeh, UC Berkeley

GrC 2010 Keynote: "Precisiation of Meaning--From Natural Language to Granular Computing"


10:30 AM - 10:50AM

Coffee Break

10:50 AM - 11:30 AM

Dr. Benjamin Reed, Yahoo!

CW 2010/NFIC keynote: "ZooKeeper"


11:30 AM - 12:00 PM

Mr. Pradeep Kathail, CTO, Cisco

"Management of Large Networks"


12:00 PM - 1:30 PM


1:30 PM - 2:00 PM

Mr. Patrick Fu, Infrastructure Software Division, CCMA ITRI

"Energy Efficient Virtual Resource Management"


2:00 PM - 2:30 PM

Dr. Chen Li, UC Irvine

"Scalable Interactive Search"


2:30 PM - 3:00 PM

Coffee Break

3:00 PM - 3:30 PM

Dr. Felix Naumann, HPI

"Extreme Web Data Integration"


3:30 PM - 4:00 PM

Dr. Rajasekar Krishnamurthy, IBM Almaden Research

"Midas: Scalable Entity Integration for Unstructured Data Sources"


1:30 PM - 5:30 PM

Parallel Sessions







8/15 GrC2010 12th NFIC 

9:00 AM - 9:45 AM

Dr. S. Felix Wu

"Relations-Oriented Social-Centric Future Internet Design"

9:45 AM - 10:30 AM

Dr. Toyoaki Nishida

"Social Intelligence Design for Cultivating Shared Situated Intelligence"

10:30 AM - 10:50AM

Coffee Break

10:50 AM - 11:35 AM

Dr. Ming Li (Killam Prize 2010 Winner)

"Information Distance from a Question to an Answer"

11:35 AM - 12:20 PM

Dr. Giovanni Seni

"On diversity, complexity and regularization in ensemble models"

12:20 PM - 1:30 PM


1:30 PM - 2:15 PM

Dr. Dimitrios Gunopulos, University of Athens

"Searching in Sequences of Documents and in Biological Sequences"

2:15 PM - 3:00 PM

Dr. Zhenyuan Wang


"Nonlinear Integrals and Their Applications in Information Fusion and Data Mining"

3:00 PM - 3:30 PM

Coffee Break

3:30 PM - 4:15 PM

Dr. Anita Wasilewska


"Descriptive Granularity"

4:15 PM - 5:00 PM

Dr. Lior Rokach

"k-Anonymized Reducts"

1:30 PM - 5:30 PM

Parallel Sessions

6:30 PM - 9:30 PM 

Banquet dinner 





8/16 GrC2010 12th NFIC 

9:00 AM - 9:45 AM

Dr. Stuart Rubin

"Microformats for Innovative Lexicons"

9:45 AM - 10:45 AM


Chair: Dr. Stuart Rubin

Dr. Lofti Zadeh
, Dr. Ashok Deshpande, Dr. Jerry M. Mendel, Dr. Anita Wasilewska, Dr. Zhenyuan Wang


10:45 AM - 11:00AM

Coffee Break

11:00 AM - 11:45 AM

Dr. Jerry M. Mendel

"Interval Type-2 Fuzzy Logic System versus Perceptual Computer: Similarities and Differences"

11:45 AM - 12:30 PM

Dr. Fei-Yue Wang, Intstitue of Automation, Chinese Academy of Science

"Linguistic Dynamic Systems for Perception-based Information: A Computational Intelligence Approach"

12:30 PM - 1:30 PM


1:30 PM - 2:15 PM

Dr. Jiali Feng

"Attribute Theory Methods in Noetic Science and Intelligence Simulation"

2:15 PM - 3:00 PM

Dr. Ashok Deshpande

"Can Fuzzy Logic Bring Complex Environmental Issues into Focus?"

3:00 PM - 3:30 PM

Coffee Break

3:30 PM - 4:15 PM

Business Meeting


1:30 PM - 5:30 PM

Parallel Sessions




Conference Speakers and Abstracts:


Dr. Lotfi Zadeh is a Professor in the Graduate School, Computer Science Division, Department of EECS, University of California, Berkeley. In addition, he is serving as the Director of BISC (Berkeley Initiative in Soft Computing). Lotfi Zadeh is an alumnus of the University of Tehran, MIT and Columbia University. He held visiting appointments at the Institute for Advanced Study, Princeton, NJ; MIT, Cambridge, MA; IBM Research Laboratory, San Jose, CA; AI Center, SRI International, Menlo Park, CA; and the Center for the Study of Language and Information, Stanford University. His earlier work was concerned in the main with systems analysis, decision analysis and information systems. His current research is focused on fuzzy logic, computing with words and soft computing, which is a coalition of fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing and parts of machine learning. Lotfi Zadeh is a Fellow of the IEEE, AAAS, ACM, AAAI, and IFSA. He is a member of the National Academy of Engineering and a Foreign Member of the Finnish Academy of Sciences, the Polish Academy of Sciences, Korean Academy of Science & Technology, the Bulgarian Academy of Sciences, the International Academy of Systems Studies, Moscow and the Azerbaijan National Academy of Sciences. He is a recipient of the IEEE Education Medal, the IEEE Richard W. Hamming Medal, the IEEE Medal of Honor, the ASME Rufus Oldenburger Medal, the B. Bolzano Medal of the Czech Academy of Sciences, the Kampe de Feriet Medal, the AACC Richard E. Bellman Control Heritage Award, the Grigore Moisil Prize, the Honda Prize, the Okawa Prize, the AIM Information Science Award, the IEEE-SMC J. P. Wohl Career Achievement Award, the SOFT Scientific Contribution Memorial Award of the Japan Society for Fuzzy Theory, the IEEE Millennium Medal, the ACM 2001 Allen Newell Award, the Norbert Wiener Award of the IEEE Systems, Man and Cybernetics Society, Civitate Honoris Causa by Budapest Tech (BT) Polytechnical Institution, Budapest, Hungary, the V. Kaufmann Prize, International Association for Fuzzy-Set Management and Economy (SIGEF), the Nicolaus Copernicus Medal of the Polish Academy of Sciences, the J. Keith Brimacombe IPMM Award, the Silicon Valley Engineering Hall of Fame, the Heinz Nixdorf MuseumsForum Wall of Fame, the Egleston Medal, the Franklin Institute Medal, other awards and twenty-five honorary doctorates. He has published extensively on a wide variety of subjects relating to the conception, design and analysis of information/intelligent systems, and is serving on the editorial boards of over seventy journals.

Abstract: "Precisiation of Meaning--From Natural Language to Granular Computing" (GrC 2010 Keynote)

Unprecisiated (raw) natural language does not lend itself to computation. Natural languages are intrinsically imprecise. A major source of imprecision is unsharpness of class boundaries. Unsharpness of class boundaries is coextensive with fuzziness. In this perspective, most human concepts are fuzzy. Everyday examples are near, fast, sweet, similar, etc. To deal with fuzzy concepts what is needed is fuzzy logic. Computing with Words is based on fuzzy logic. A CW engine has two principal components: a Precisiation module and a Computation module. The function of the Precisiation module is that of constructing a computational model of the information, I, which is to be computed with. In CW, a computational model of a proposition, p, drawn from a natural language, is represented as a generalized constraint. Precisiated I is the input to the Computation module. Computation is carried out through propagation and counterpropagation of generalized constraints. What comes into play at this stage is the machinery of Granular Computing, GrC. In this machinery, a principal tool is the Extension Principle of fuzzy logic. Application of this principle reduces the problem of computation with natural language to that of solving a mathematical program.

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Dr. Benjamin Reed has worked for two decades in industry. He started as an intern working on CAD/Cam systems. From there his career led him to Shipping and Receiving applications in OS/2, AIX, and CICS, to Operations, to System Admin Research and Java Frameworks at IBM Almaden Research (11 years), and finally to Yahoo! Research (3 years ago) working on the largest Distributed Computing Problems. His main interests now are large scale processing environments and highly available and scalable systems.

Abstract: "Zookeeper"

Large distributed systems, aka Cloud Computing, are a Zoo: machines being added and removed, configuration changes, usage spikes, and load balancing; distributed applications must also handle failures such as network partitions and crashes. We developed ZooKeeper to help the distributed application developer build applications in this chaotic environment. It provides a simple abstraction for coordination that developers can use extensively to handle changes and failures. In our experience, applications that use ZooKeeper are not only more robust but also easier to develop than those using ad-hoc solutions. This talk will motivate the design of ZooKeeper, show how it is used, and share insights gained from its use in production.

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Mr. Pradeep Kathail, 20+ year industry veteran, is the CTO for Network Software and Solutions technology Group of Cisco and is responsible for technology strategy and software architecture. Before his current assignment, he held the position of Cisco Distinguished Engineer and during his tenure at Cisco, Pradeep has developed large scale router and switch software for high-end platforms. Prior to Cisco, Pradeep held various technology management jobs at Apple, Novell, SITA and IBM designing, developing and maintaining large or ultra large scale systems. He holds a MS Computer Science degree from IIT Roorkee, India and is a member of ACM and IEEE.

Abstract: "Management of Large Networks"

Continuous growth of internet and new green field usage like Smart Grid is challenging the traditional centralized way of managing the networks. Network management needs to be more granular and network devices need to make some autonomous decisions in consultation with the neighboring device within the policy set by central management entity. This new paradigm will distribute the management load, and make the network truly self-healing.

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Mr. Patrick Fu has 20 years of Software industry experience. He has managed and successfully delivered multiple large-scale complex software development projects since 1988. Before joining ITRI, Patrick was the VP of Engineering for Interwoven Inc., responsible for their Web Content Management Engineering team, with annual revenue of US$80 million. Prior to Interwoven, Patrick was a Senior Development Manager at Sun Microsystems Inc., where he managed multiple Networking related projects. Specifically, Patrick initiated the Solaris Clustering project, where he build a team that covers both Engineering and QA for Solaris Clustering development. Patrick was also a development manager at Amdahl Inc. from 1988 through 1995, where he managed Macrocode development group, responsible for the delivery of Multiple Domain Feature on Amdahl machines. Prior to entering Management, Patrick was a MVS design and TPF software developer with IBM Corp. Patrick received his M.S. degree in Computer Science from State University of New York. He received his BSEE degree from National Taiwan University.

Abstract: "Energy Efficient Virtual Resource Management"

Taiwan has long been very successful in its OEM/ODM business for building Enterprise class servers. ITRI sees an opportunity for Taiwan's ODM industry to elevate itself and build a complete solution for Cloud Computing. This will enable service providers and data center operators to quickly launch an "Infrastructure Cloud" based on commodity hardware at a significantly lower cost. Thus, CCMA @ ITRI (Cloud-Computing Center for Mobile Application) was founded in September, 2009. One of the projects CCMA will be working on is Cloud OS. Cloud OS includes many components to efficiently manage virtual and physical resources in the "Infrastructure Cloud" mentioned above. This talk focuses, in particular, on the Resource Monitoring component of Cloud OS and how it leverages the virtualization platform to manage a Virtual Data Center and optimize the use of its resources. Cloud OS has built in triggering mechanisms to develop a virtual resource consolidation plan and migrate virtual resources onto under-utilized hardware to optimize energy usage in the Cloud OS "Infrastructure Cloud".

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Dr. Chen Li is an associate professor in the Department of Computer Science at the University of California, Irvine. He received his Ph.D. degree in Computer Science from Stanford University in 2001, and his M.S. and B.S. in Computer Science from Tsinghua University, China, in 1996 and 1994, respectively. He received a National Science Foundation CAREER Award in 2003 and a few other NSF grants and industry gifts. He was once a part-time Visiting Research Scientist at Google. His research interests are in the fields of data management and information search, including text search, data cleansing, and data integration. He is a founder of

Abstract: "Scalable Interactive Search"

Traditional information systems return answers after a user submits a complete query. Users often feel "left in the dark" when they have limited knowledge about the underlying data, and have to use a try-and-see approach for finding information. A recent trend of supporting autocomplete in these systems is a first step towards solving this problem. In this talk we will discuss a new information-access paradigm, called "interactive search" or "search as you type," which allows users to search and explore underlying data as they type in query keywords. We focus on how to answer such search queries on large data sets efficiently (within milliseconds per query) in order to achieve an interactive speed. For illustration purposes, we will demonstrate several systems powered by these techniques.

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Dr. Felix Naumann studied mathematics, economy, and computer sciences at the University of Technology in Berlin. After receiving his diploma (MA) in 1997 he joined the graduate school "Distributed Information Systems" at Humboldt University of Berlin. He completed his PhD. thesis on "Quality-driven Query Answering" in 2000. In 2001 and 2002 he worked at the IBM Almaden Research Center on topics around data integration. From 2003 - 2006 he was assistant professor for information integration at the Humboldt-University of Berlin. Since 2006 he holds the chair for information systems at the Hasso Plattner Institute at the University of Potsdam in Germany.

Abstract: "Extreme Web Data Integration"

The wealth of freely available, structured information on the Web is constantly growing. This is especially true for public data from and about governments and administrations. Data-providing projects, such as DBpedia and Freebase from the linked open data community, as well as structured data from domain-specific sites, such as or, make it possible to integrate data from multiple sources and thus create new data sets with added value. The talk highlights the extreme heterogeneities of such web data and points to methods to overcome them: To make use of this data and create added value for a given domain of interest, a multitude of tasks must be completed: Source selection to identify appropriate and high quality sources, data extraction to create structured data, scrubbing to standardize and clean data, entity matching to associate different occurrences of the same entity, and finally data transformation and data fusion to combine all data about an entity in a single, consistent representation.

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Dr. Rajasekar Krishnamurthy is a Research Staff Member in the Intelligent Information Integration group at IBM Research-Almaden. He received a B.Tech in Computer Science and Engineering from the Indian Institute of Technology-Madras in 1998, and a Ph.D. degree in Computer Science from the University of Wisconsin-Madison in 2004. His research interests are primarily in the integration of structured and unstructured data, with emphasis on information extraction, entity resolution and data cleansing.

Abstract: "Midas: Scalable Entity Integration for Unstructured Data Sources"

There are a large number of publicly available data sources containing rich information about entities, relationships and events. For instance, publicly traded companies file documents periodically with regulatory agencies such as SEC and FDIC describing their financial activities and their relationships with other companies and people. While this information is of crucial interest to investors, financial analysts and bankers, accessing the wealth of structured entity information buried in unstructured text is a non-trivial task. The primary goal of the Midas project is to address scenarios such as the above that depend on large-scale unstructured entity integration. To address this challenge, we are building a system that enables easy and scalable integration of unstructured and semi-structured information present across multiple data sources. In this talk, we highlight some of the main technological challenges that need to be addressed in order to transform the data from a document or record view of the world to an entity-centric view, where multiple facts about the same real-world entity are merged into one object with, ideally, clean and complete attributes. The main challenges addressed by Midas are (a) unstructured information extraction (e.g., extraction of various facts from the multitude of text or html documents), (b) entity integration (resolving and merging references to the same real-world entity and creating correct relationships among the resulting objects) and (c) scalable platform (building a scalable Hadoop-based system for processing large volumes of data in an incremental fashion).

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Dr. S. Felix Wu has been doing 'experimental' system research, i.e., building prototype systems to justify and validate novel architectural concepts. Since 1995, he and his students/postdocs have built many experimental systems in the areas of fault tolerant network, IPSec/VPN security policy, attack source tracing, wireless network security, intrusion detection and response, and online social network systems. His research has made real impacts to the Internet community. As an example, in 1996, his research team discovered and announced a critical flaw on most commercial OSPF (Open Shortest Path First) routers. In 2000, when DDoS (Distributed Denial of Services) attacks disabled many commercial web sites, his IPSec-based DECIDUOUS (DECentralized IDentification of intrUsion sOUrceS) system brought several attentions by demonstrating its capability to partition DDoS attack flows. His most recent works are (1) developing new virtual machine technologies to enhance system security, and (2) leveraging online social network as the key to re-design the Internet architecture (the DSL project: Davis Social Links). The latter is currently being supported by NSF/FIND, NSF/BBN/GENI, US. Army/ARO MURI, and the newly awarded ARL's Network Science CTA. Prof. Wu received his BS from Tunghai University, Taiwan, in 1985, and PhD from Columbia University in 1995, all in Computer Science. He currently has 100+ conference and journal publications.

Abstract: "Relationship-Oriented Social-Centric Future Internet Design"

Online Social Networks (OSN) such as Facebook are growing rapidly. On one hand, OSN is invaluable in supporting communication for our Internet-based community, as an example, if many consider stealing vegetables from friends is also one interesting form of social communication activities. On the other hand, the illness of OSN design is the root cause for losing its value. In this talk, we will address how to leverage OSN infrastructure to solve security problems and how to protect the value of OSN such that we might not introduce new security problems. I will discuss the rationale and design principles behind Davis Social Links (DSL), a FIND (Future INternet Design) and GENI (Globel Environment for Network Innovation) project sponsored by NSF. In particular, under the consideration of re-designing the Internet, I would argue that network-layer unique identifiers and global connectivity by default, both being the fundamental design principles for our current Internet, might be both unnecessary and harmful.

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Dr. Toyoaki Nishida is Professor at Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University. He received the B.E., the M.E., and the Doctor of Engineering degrees from Kyoto University in 1977, 1979, and 1984, respectively. His research centers on artificial intelligence and human computer interaction. He founded an international workshop series on social intelligence design in 2001. Major works in social intelligence design have been published in several special issues of the AI & Society journal. He opened up a new field of research called conversational informatics in 2003. He collected and compiled representative works in conversational informatics as: Nishida (ed.) Conversational Informatics -- An Engineering Approach, Wiley, 2007. Currently, he leads several projects related to social intelligence design and conversational informatics. He serves for numerous academic activities, including the president of JSAI (Japanese Society for Artificial Intelligence), an associate editor of the AI & Society journal, an area editor (Intelligent Systems) of the New Generation

Abstract: "Social Intelligence Design for Cultivating Shared Situated Intelligence"

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Dr. Ming Li is a Canada Research Chair in Bioinformatics and a University Professor at the University of Waterloo. He is a fellow of Royal Society of Canada, ACM, and IEEE. He is a recipient of Canada's E.W.R. Steacie Fellowship Award in 1996, the 2001 Killam Fellowship and the 2010's Killam Prize. Together with Paul Vitanyi they have pioneered the applications of Kolmogorov complexity and co-authored the book "An introduction to Kolmogorov complexity and its applications". His research interests recently include protein structure determination and next generation internet search engine.

Abstract: "Information Distance from a Question to an Answer"

In physical world, we know how to measure distance between Waterloo and Athens. However, have you thought about how to measure the "informational distance" between two genomes, two pictures, two English texts, two words, two concepts, and between a query and an answer? We develop a general theory of information distance to measure the distance between any two information carrying entities. We will show that our theory is "better" than any other theory that satisfy reasonable conditions. Then we show how such a theory can be effectively used in many applications, as particularly, in a query-answer system.

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Dr. Giovanni Seni is a Senior Scientist with Elder Research, Inc. and directs ERI's Western office. As an active data mining practitioner in Silicon Valley, he has over 15 years R&D experience in statistical pattern recognition, data mining, and human-computer interaction applications. He has been a member of the technical staff at large technology companies, and a contributor at smaller organizations. He holds five US patents and has published over twenty conference and journal articles. His book with John Elder, "Ensemble Methods in Data Mining - Improving accuracy through combining predictions", was published in February 2010 by Morgan & Claypool. Giovanni is an adjunct faculty at the Computer Engineering Department of Santa Clara University, where he teaches an Introduction to Pattern Recognition and Data Mining class.

Abstract: "On diversity, complexity and regularization in ensemble models"

The discovery of ensemble methods is one of the most influential developments in Data Mining and Machine Learning in the past decade. These methods combine multiple models into a single predictive system that is more accurate than even the best of its components. The use of ensemble methods can provide a critical boost to existing systems addressing the hardest of industrial challenges - from investment timing to drug discovery, from fraud detection to recommendation systems - where predictive accuracy is vital. This talk, based on a recently published book by the speaker, offers a concise introduction to this breakthrough topic. After a sketch of the major concerns in predictive learning, the talk will give an overview of regularization, a key concept driving the superior performance of modern ensembling algorithms. It then takes a shortcut into the heart of the popular tree-based ensemble creation strategies using recent developments from the frontiers of statistics, where research efforts are now focused to explain and harness the mysteries of ensembles.

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Dr. Dimitrios Gunopulos got his PhD from Princeton University in 1995. He has held positions as a Postoctoral Fellow at the Max-Planck-Institut for Informatics, Research Associate at the IBM Almaden Research Center, Visiting Researcher at the University of Helsinki, Assistant, Associate, and Full Professor at the Department of Computer Science and Engineering in the University of California Riverside, and Associate Professor in the Department of Informatics and Telecommunications, University of Athens. His research is in the areas of Data Mining, Knowledge Discovery in Databases, Databases, Sensor Networks, Peer-to-Peer systems, and Algorithms. He has co-authored over a hundred journal and conference papers that have been widely cited and a book. He has supervised 8 Ph.D. theses and 17 MS. His research has been supported by NSF (including an NSF CAREER award), the DoD, the Institute of Museum and Library Services, the Tobacco Related Disease Research Program, the European Commission, AT&T and Nokia. He has served as a General co-Chair in IEEE ICDM 2011, as a PC co-Chair in ECML/PKDD 2011, IEEE ICDM 2008, ACM SIGKDD 2006, SSDBM 2003, and DMKD 2000, and as an associate Editor at IEEE TKDE, at IEEE TPDS, and at ACM TKDD.

Abstract: "Searching in Sequences of Documents and in Biological Sequences"

We consider the problem of searching in two domains where the ordering is important, namely biological sequence data, and data from live, time-stamped data collections (such as blogs). As the number and size of such data collections increase, the problem of efficiently indexing and searching such data becomes more important. We present novel approaches for subsequence matching and for keyword search and event identification in document sequences.

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Dr. Zhenyuan Wang graduated from Fudan University, Shanghai, China in 1962. He received his Ph.D. from the Department of Systems Science, State University of New York at Binghamton in 1991. He taught various mathematical courses in Hebei University for many years since 1962, supervised graduate students since 1978, and served as the Chair of the Mathematics Department there from 1985 to 1990. He was a visiting scholar, visiting professor, or research fellow in University Paris VI, Binghamton University (SUNY), Chinese University of Hong Kong, New Mexico State University, and University of Texas at El Paso during the period from 1979 to 2008. He has been serving as a professor in the Department of Mathematics, University of Nebraska at Omaha since 2003. His research interests are nonadditive measures, nonlinear integrals, probability and statistics, optimization, soft computing, and data mining. He is the author or a co-author of more than 150 research papers and three monographs: "Fuzzy Measure Theory" (1992), "Generalized Measure Theory" (2008), and "Nonlinear Integrals and Their Applications in Data Mining" (2010). He received a number of honors and awards including the title of "National expert" from the Chinese National Scientific and Technological Commission in 1986 and the "Citation Classic Award" from the Institute for Scientific Information (USA) in 2000.

Abstract: "Nonlinear Integrals and Their Applications in Information Fusion and Data Mining"

Regarding the set of considered predictive attributes (or feature attributes) as the universal set, nonadditive set functions defined on its power set can be used to describe the interaction among the contributions from various predictive attributes towards a given objective attribute. Relevantly, the classical linear aggregation tool that can be expressed as a linear integral defined on the universal set should be generalized to be a nonlinear integral. The Choquet integral, the upper integral, and the lower integral are the common types of nonlinear integrals. Using nonlinear integrals, some classical models in data mining, such as the multiregression and the classification, can be generalized as well. Once the necessary data are available, the values of unknown parameters in these nonlinear models can be optimally determined through some soft computing techniques approximately. Since the above-mentioned interaction can be painstakingly captured, the introduced new nonlinear models are powerful.

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Dr. Lior Rokach:

Abstract: "k-Anonymized Reducts"

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Dr. Stuart H. Rubin (M'88-SM'00) is a senior scientist at the Space and Naval Warfare Systems Center (SSC) in San Diego, code 56340, and a fellow of the Society for Information Reuse and Integration. He was previously a tenured Associate Professor of computer science at Central Michigan University (CMU). He has since given plenary speeches at numerous international conferences, founded and currently serves as general chair of the IEEE Information Reuse and Integration (IRI) conference, previously the IEEE North American Fuzzy Information Processing Society (NAFIPS) conference, mentored several post-docs, and supervised numerous MS Theses and independent studies. His current interests include computational creativity, computing with words, and knowledge-discovery systems. Dr. Rubin was previously an ONT post-doctoral fellow at the Naval Command, Control, and Ocean Surveillance Center (NCCOSC). He received a BS from the University of Rhode Island, Magna Cum Laude in 1975, an MSISE in systems engineering from Ohio University in 1977, and an MS in computer science from Rutgers University in 1980. He received his Ph.D. from Lehigh University in Bethlehem, PA in 1988. Dr. Rubin's Ph.D. thesis was entitled, "On the transformative compression of coherent languages". His dissertation was selected for novel AI content by SIGART in January, 1989. Dr. Rubin received SSC-PAC's Publication of the Year Award in 2007, 2009, and 2010. Dr. Rubin was awarded the US Government Certificate of Merit in 1987 for his technical work on the Very High-Speed Integrated Circuits (VHSIC) program. He received the Navy Award of Merit for Group Achievement in 2002. Dr. Rubin chairs the IEEE System, Man, and Cybernetics (SMC) Committee on knowledge acquisition in intelligent systems and has served on the IEEE Board of Governors. He currently serves as the IEEE SMC industrial and AAAI liaison. He also serves as an Associate Editor for the IEEE SMC:C Transactions. He is the author of over 220 refereed papers and book chapters as well as numerous patents, patents pending, and patent disclosures.

Abstract: "Microformats for Innovative Lexicons"

A microformat is a set of design principles for including semantic information within standard X/HTML markup. Individual microformat entities are distributed yet share a common semantics. Each microformat is a granule of structured information containing a set of attributes. These information granules can be produced, distributed, aggregated, and consumed without reliance on centralized services. We describe the impact on the gathering, distribution, and analysis of concepts within our visual communication research. In this paper we present solutions for managing lexical consistency when microformat-structured information granules are distributed and maintained independently and asynchronously. Lexical groups and hierarchies leverage the resulting inconsistencies, utilizing term aggregation across visual and linguistic features to dynamically compose lexicons and to perform lexical analysis. We think of this as creating semantic and orthographic 'projections' of the lexicon into different feature spaces. We show how to use this approach to construct situated lexicons which derive from shared context and social communities.

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Dr. Anita Wasilewska is a representative of the Polish School of Mathematics. She is a direct Ph.D. descendant of Alfred Tarski (Warsaw, Berkley). Conequently though one of the founders of the Polish School of Mathemathics Kazimierz Twardowski (Vienna, Warsaw) she is also a direct Ph.D. descendant of Nicolaus Copernicus (Mikolaj Kopernik), Jurisutriusque Doctor Uniwersytet Jagiellonski, Universita di Bologna, Universita degli Studi di Ferrara, Universita di Padova 1499, as well as Gottfried Leibniz, Ph.D. 1666, Immanuel Kant, Ph.D. 1770, and Desiderius Erasmus of Rotterdam, Theologiae Baccalaureus, 1497. Her other famous direct ancestors include Andrei Markov, Pafnuty Chebyshev, Emile Borel, Henri Lebesgue, Joseph Lagrange, Ganston Darboux, Pierre-Simon Laplace, Jean Le Rond d'Alembert and Leonhard Euler. She earned her master Degree in Computer Science (professor Z. Pawlak) and Ph.D. in Mathematics (professor H. Rasiowa) from Warsaw University, where she was a faculty of Mathematics Department 1967-1983. She came to the United States in 1980 as a visiting Assistant Professor in Mathematics at Wesleyan and Yale Universities in Connecticut before joining Stony Brook's Department of Computer Science in 1986. Her latest research interests are in Granular Computing and Foundations Data Mining. She has published papers in many domains ranging from Classical and Non- Classical Logics, Automated Theorem Proving, Formal languages, Theory of Programs, Foundations of Rough Sets in which she was one of the pioneers, to generalized Fuzzy and Rough sets, Machine Learning and Mobile Computing for Global World.

Abstract: "Descriptive Granularity"

We define a notion of a descriptive granularity and present its formal syntax and semantics. We do so in terms of three abstract models: Descriptive, Semantic, and Granular. The descriptive model formalizes the syntactical concepts and properties of the data mining, or learning process. Semantic model formalizes its semantical properties. The Granular model establishes a relationship between the Descriptive and Semantic models in terms of a formal satisfaction relation.

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Dr. Jerry M. Mendel received the Ph.D. degree in electrical engineering from the Polytechnic Institute of Brooklyn, Brooklyn, NY. Currently he is Professor of Electrical Engineering and Systems Architecting Engineering at the University of Southern California in Los Angeles, where he has been since 1974. He has published over 500 technical papers and is author and/or editor of ninet books, including Uncertain Rule-based Fuzzy Logic Systems: Introduction and New Directions (Prentice-Hall, 2001) and Perceptual Computing: Aiding People in Making Subjective Judgments (Wiley & IEEE Press, 2010). His present research interests include: type-2 fuzzy logic systems and their applications to a wide range of problems, including smart oil field technology and computing with words. He is a Life Fellow of the IEEE, a Distinguished Member of the IEEE Control Systems Society, and a Fellow of the International Fuzzy Systems Association. He was President of the IEEE Control Systems Society in 1986. He was a member of the Administrative Committee of the IEEE Computational Intelligence Society (2004-2009) and was Chairman of its Fuzzy Systems Technical Committee. Among his awards are the 1983 Best Transactions Paper Award of the IEEE Geoscience and Remote Sensing Society, the 1992 Signal Processing Society Paper Award, the 2002 Transactions on Fuzzy Systems Outstanding Paper Award, a 1984 IEEE Centennial Medal, an IEEE Third Millenium Medal, a Fuzzy Systems Pioneer Award (2008) from the IEEE Computational Intelligence Society, and a Pioneer Award from the IEEE Granular Computing Conference, May 2006, for Outstanding Contributions in Type-2 Fuzzy Systems.

Abstract: "Interval Type-2 Fuzzy Logic System versus Perceptual Computer: Similarities and Differences"

Interval type-2 fuzzy logic systems (IT2 FLSs) fall into the category of "function approximation", and are widely used in fuzzy logic control, rule-based classification, signal processing, etc. On the other hand, a Perceptual Computer (Per-C) is an implementation of Zadeh's Computing With Words paradigm, and is used to aid people in making subjective judgments. This talk will, for the first time, explain the similarities (which are few) and the differences (which are many) between these two systems. It will do this by focusing on the inputs, outputs and components of an IT2 FLS and Per-C, contrasting them side-by side. Such comparisons are needed so that the Per-C is not confused with an IT2 FLS.

Slide for the talk

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Dr. Fei-Yue Wang received Ph.D. in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, New York in 1990. He jointed University of Arizona in 1990 and became a Professor and Directors of the Robotics and Automation Lab and the Program in Advanced Research for Complex Systems. In 1999, he found Intelligent Control and Systems Engineering Center at Chinese Academy of Sciences (CAS) under the support of Outstanding Oversea Chinese Talents Program. Since 2002, he is the Director of Key Lab of Complex Systems and Intelligence Science at CAS. Currently, he is the Dean of School of Software Engineering, Xi'an Jiaotong University, and Vice President of the Institute of Automation, CAS. His major research interests include social computing, web science, complex systems, computational intelligence, intelligent systems and control. From 1995-2000, Dr. Wang was the Editor-in-Chief of Int'l J. of Intelligent Control and Systems and Series in Intelligent Control and Intelligent Automation. Currently, he is the Editor in Chief of IEEE Intelligent Systems and IEEE Transactions on Intelligent Transportations Systems. He has served as Chairs of more than 20 IEEE, ACM, INFORMS, and ASME Conferences. He was the President of IEEE ITS Society from 2005-2007, Chinese Association for Science and Technology in 2005, and American Zhu Kezhen Education Foundation from 2007-2008. From 2006-2008, Dr. Wang was the Founding President of ACM Beijing Chapter. Currently he is an ACM Council Member at Large, a member on the WSRI Scientific Council, and Vice President and Secretary-General of Chinese Association of Automation. Dr. Wang is member of Sigma Xi and an elected Fellow of IEEE, INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China and awarded the Outstanding Scientist by ACM for his work in intelligent control and social computing.

Abstract: "Linguistic Dynamic Systems for Perception-based Information: A Computational Intelligence Approach"

Linguistic Dynamic Systems (LDS) provide a computational and dynamic framework to process perception-based information in general and support computing with words as well as grannular computing in particular. This paper presents a comprehensive review of historical developments and current LDS works as well as their relationship with other computational intelligence approaches, such as fuzzy logic, type 2 fuzzy sets, neural networks, evolutionary algorithms, and granular computing. Extension principle is used to generalize the concepts and methods of conventional dynamic systems (CDS) into their LDS counterparts. Detailed numerical examples are constructed to illustrate, analyze, and compare properties of various CDS and LDS problems. Issues on the future LDS development are addressed and a corresponding research roadmap has been proposed for further discussion. We believe that, as social and human behaviors become an increasingly important dimension in modeling real-world problems and complex systems, LDS will play a key role in constructing intelligent human machine interface in particular and developing next generation intelligent systems in general.

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Dr. Jiali Feng is currently a full professor at the College of Information Engineering at Shanghai Maritime University. He got his B.S in Mathematics in the Mathematics Department at Guangxi Normal University, in Guilin, Guangxi, China, in 1982 and his PhD in radioprotection at China Institute of Atomic Energy in 2001. His research is focused on the attribute theory method for thinking constructing and intelligence modeling which relating to Artificial Intelligence, Artificial Neuron Network, Genetic Arithmetic, Pattern Recognition, and etc. Since 2000 he is a Professor in Department of Computer Science at Shanghai Maritime University, and served as dean of College of Information Engineering at the University from 2003 to 2005. He is a pluralistic professor of Academy of Disaster Reduction and Emergency Management, Ministry of Affairs of china & Ministry of Education of China, at Beijing Normal University from 2007. Dr. Feng is deputy director of Machine Learning Society, Chinese Association for Artificial Intelligence. Member of IEEE Shanghai Section. He served as co-chair of the 15th Conference on Artificial Neural Network of China, 2006; the Chair of the Program Committee of the First International Conference on Risk Analysis and Crisis Response,2007; Vice Chairs of IEEE GrC 2008, International Conference on Granular Computing, the Chair of the Program Committee of 2007 Joint Rough Set Symposium.

Abstract: "Attribute Theory Methods in Noetic Science and Intelligence Simulation"

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Dr. Ashok Deshpande holds a PhD degree in Engineering and Technology and was Deputy Director at National Environmental Engineering Research Institute (NEERI) Nagpur. He has a specialization in environmental engineering at his master degree from University of Roorkee (now IITR), and has over 4 decades of experience in R&D and has over 150 publications in the National and International Journals of repute, and his initial R&D experience were primarily on some of the important facets of environmental engineering including mathematical modeling but got interested in soft computing with focus on fuzzy logic in early 80's. In the past Dr. Ashok was WHO Adviser, Common Wealth Science Council Resource Scientist, World Bank Project Director for the studies on Probabilistic Risk Assessment for Chemical Process industry. He also organized a Workshop as WHO Adviser in 5 countries on Unaccounted for Water Management and also assisted Danish International Development Authority (DANIDA) as a Project Advisor. More importantly, Professor Lotfi Zadeh, the founder of fuzzy logic, after listening to many seminar talks, asked Professor Ashok Deshpande to be the Chair of Berkeley Initiative in Soft Computing (BISC)-Special Interest Group (SIG)-Environment Management Systems (EMS). He was invited by the International Atomic Energy Agency (IAEA) as an expert for organizing a Training Program at CDTN, Brazil (2004 and 2006) on Fuzzy logic with applications In March 2008, Professor Deshpande organized a Training workshop on Fuzzy sets and Fuzzy logic with Applications at the University of Illinois Chicago USA which was highly appreciated by all. In 2008 the similar workshop was organized at Kathmandu Nepal. Dr. Deshpande's passion and mission is to propagate the use of fuzzy logic nationally and internationally. Presently he is an Adjunct Professor in Bioinformatics Center of University of Pune and at also at College of Engineering Pune and PhD supervisor and examiner. At present, his doctoral students work only on fuzzy logic related topics.

Abstract: "Can Fuzzy Logic Bring Complex Environmental Issues into Focus?"

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Last update: 28 Jul 2011