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Abstract

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.

Editor

Patel-Schneider, P.F. et. al

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Abstract

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.

Editor

Patel-Schneider, P.F. et. al

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Date

23. 3.2008 19:10:22

Editor

Fayyad, U. et al.

Footnote

Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.

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Content

Inhalt: Tim Bemers-Lee: The Original Dream - Re-enter Machines - Where Are We Now? - The World Wide Web Consortium - Where Is the Web Going Next? / Dieter Fensel, James Hendler, Henry Lieberman, and Wolfgang Wahlster: Why Is There a Need for the Semantic Web and What Will It Provide? - How the Semantic Web Will Be Possible / Jeff Heflin, James Hendler, and Sean Luke: SHOE: A Blueprint for the Semantic Web / Deborah L. McGuinness, Richard Fikes, Lynn Andrea Stein, and James Hendler: DAML-ONT: An Ontology Language for the Semantic Web / Michel Klein, Jeen Broekstra, Dieter Fensel, Frank van Harmelen, and Ian Horrocks: Ontologies and Schema Languages on the Web / Borys Omelayenko, Monica Crubezy, Dieter Fensel, Richard Benjamins, Bob Wielinga, Enrico Motta, Mark Musen, and Ying Ding: UPML: The Language and Tool Support for Making the Semantic Web Alive / Deborah L. McGuinness: Ontologies Come of Age / Jeen Broekstra, Arjohn Kampman, and Frank van Harmelen: Sesame: An Architecture for Storing and Querying RDF Data and Schema Information / Rob Jasper and Mike Uschold: Enabling Task-Centered Knowledge Support through Semantic Markup / Yolanda Gil: Knowledge Mobility: Semantics for the Web as a White Knight for Knowledge-Based Systems / Sanjeev Thacker, Amit Sheth, and Shuchi Patel: Complex Relationships for the Semantic Web / Alexander Maedche, Steffen Staab, Nenad Stojanovic, Rudi Studer, and York Sure: SEmantic portAL: The SEAL Approach / Ora Lassila and Mark Adler: Semantic Gadgets: Ubiquitous Computing Meets the Semantic Web / Christopher Frye, Mike Plusch, and Henry Lieberman: Static and Dynamic Semantics of the Web / Masahiro Hori: Semantic Annotation for Web Content Adaptation / Austin Tate, Jeff Dalton, John Levine, and Alex Nixon: Task-Achieving Agents on the World Wide Web

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Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

Editor

Stamou, G. u. S. Kollias

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Issue

Aus d. Amerikan. von U. Enderwitz u. M. Noll.

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Footnote

Rez. in: JASIS 45(1994) no.3, S.220-221 (P. Wilson)

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Content

Enthält auch die Beiträge: BROOKS, R.A.: Künstliche Intelligenz und Roboterentwicklung - RITTER, H.: Die Evolution der künstlichen Intelligenz - ENGEL, A.K. u. W. SINGER: Neuronale Grundlagen des Bewußtseins - METZINGER, T.: Postbiotisches Bewußtsein: wie man ein künstliches Subjekt baut - und warum wir es nicht tun sollten - HARA, F.: Gesichtsrobotik und emotional computing

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Editor

Staab, S. u. R. Studer

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Abstract

For more than 25 years, Hofstadter has been explaining the mystery of human consciousness through a bold fusion of mathematical logic and cognitive science. Yet for all of the acclaim his fusion has garnered (including the Pulitzer for his Godel, Escher, Bach, 1979), this pioneer admits that few readers have really grasped its meaning. To dispel the lingering incomprehension, Hofstadter here amplifies his revolutionary conception of the mind. A repudiation of traditional dualism--in which a spirit or soul inhabits the body--this revolutionary conception defines the mind as the emergence of a neural feedback loop within the brain. It is this peculiar loop that allows a stream of cognitive symbols to twist back on itself, so creating the self-awareness and self-integration that constitute an "I." Hofstadter explains the dynamics of this reflective self in refreshingly lucid language, enlivened with personal anecdotes that translate arcane formulas into the wagging tail on a golden retriever or the smile on Hopalong Cassidy. Nonspecialists are thus able to assess the divide between human and animal minds, and even to plumb the mental links binding the living to the dead. Hofstadter's analysis will not convince all skeptics. But even skeptics will appreciate the way he forces us to think deeper thoughts about thought.

Footnote

Gewisse Themen können Hofstadters Zorn erregen, zum Beispiel die Diskussion über das so genannte inverted spectrum paradox. Wie kann ich sicher sein, dass ein anderer Mensch das, was ich als Rot erlebe, genauso erlebt wie ich und nicht etwa eine Empfindung hat, die ich als Blau bezeichnen würde? Oder das Konzept vom Zombie, einem Wesen, das sich in jeder Hinsicht so verhält wie ein gewöhnlicher Mensch, dem aber alle menschlichen Gefühle fehlen. Oder Bewusstsein und freier Wille. Hofstadter hält beides für Illusionen, für Trugbilder gleich der Murmel im Briefumschlagstapel, allerdings für unvermeidbare, machtvolle Trugbilder. Wir erleben, dass ein Ich in unserem Schädel steckt, aber das ist nur eine Illusion, die von Millionen kleiner Schleifen erzeugt wird, »einem Schwarm bunter Schmetterlinge in einem Obstgarten«. An dieser Stelle ist Hofstadter anderer Meinung als sein Freund, der Philosoph Daniel C. Dennett (mit dem zusammen er das Buch »The Mind's I«, deutsch »Einsicht ins lch«, herausgegeben hat). Aber wie Den-nett, der einem seiner Werke den dreisten Titel »Consciousness Explained« gab, glaubt er, er habe das Bewusstsein erklärt. Das stimmt leider nicht. Beide haben das Bewusstsein nur beschrieben. Einen Regenbogen zu beschreiben ist einfach, ihn zu erklären ist nicht so einfach. Bewusstsein zu beschreiben ist einfach, aber das Wunder zu erklären, durch das ein Haufen Moleküle es hervorbringt, ist nicht so einfach. Ich will meine Karten auf den Tisch legen. Ich gehöre zu der kleinen Gruppe der »Mysterianer«, zu denen auch die Philosophen John R. Searle (der Schurke in Hofstadters Buch), Thomas Nagel, Colin McGinn und Jerry Fodor sowie der Linguist Noam Chomsky, der Mathematiker Roger Penrose und einige andere zählen. Wir sind der Überzeugung, dass kein heute lebender Philosoph oder Naturwissenschaftler auch nur die nebelhafteste Ahnung davon hat, wie Bewusstsein und sein unzertrennlicher Begleiter, der freie Wille, aus einem materiellen Gehirn entstehen (was sie zweifellos tun). Wir sind überzeugt, dass kein Computer, wie wir ihn heute kennen - das heißt, der aus Schaltern und Verbindungsdrähten gebaut ist -, je ein Bewusstsein dessen erlangen wird, was er tut. Das stärkste Schachprogramm wird nicht wissen, dass es Schach spielt, ebenso wenig wie eine Waschmaschine weiß, dass sie Wäsche wäscht.

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Date

21. 3.2008 19:10:22

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Editor

Kruk, S.R. u. B. McDaniel

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Editor

Goh, D. u. S. Foo