Search (4 results, page 1 of 1)

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Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

Footnote

Rez. in: JASIST 58(2007) no.3, S.457-458 (A.M.A. Ahmad): "The concept of the semantic web has emerged because search engines and text-based searching are no longer adequate, as these approaches involve an extensive information retrieval process. The deployed searching and retrieving descriptors arc naturally subjective and their deployment is often restricted to the specific application domain for which the descriptors were configured. The new era of information technology imposes different kinds of requirements and challenges. Automatic extracted audiovisual features are required, as these features are more objective, domain-independent, and more native to audiovisual content. This book is a useful guide for researchers, experts, students, and practitioners; it is a very valuable reference and can lead them through their exploration and research in multimedia content and the semantic web. The book is well organized, and introduces the concept of the semantic web and multimedia content analysis to the reader through a logical sequence from standards and hypotheses through system examples, presenting relevant tools and methods. But in some chapters readers will need a good technical background to understand some of the details. Readers may attain sufficient knowledge here to start projects or research related to the book's theme; recent results and articles related to the active research area of integrating multimedia with semantic web technologies are included. This book includes full descriptions of approaches to specific problem domains such as content search, indexing, and retrieval. This book will be very useful to researchers in the multimedia content analysis field who wish to explore the benefits of emerging semantic web technologies in applying multimedia content approaches. The first part of the book covers the definition of the two basic terms multimedia content and semantic web. The Moving Picture Experts Group standards MPEG7 and MPEG21 are quoted extensively. In addition, the means of multimedia content description are elaborated upon and schematically drawn. This extensive description is introduced by authors who are actively involved in those standards and have been participating in the work of the International Organization for Standardization (ISO)/MPEG for many years. On the other hand, this results in bias against the ad hoc or nonstandard tools for multimedia description in favor of the standard approaches. This is a general book for multimedia content; more emphasis on the general multimedia description and extraction could be provided.

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Date

23. 3.2008 19:10:22

Footnote

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.
With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."

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Editor

Staab, S. u. R. Studer

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Footnote

Rez. in Spektrum der Wissenschaft 2007, H.9, S.93-94 (M.Gardner): "Unser Gehirn enthält einige hundert Mil-liarden Neuronen mit zehntausendmal so vielen Verbindungen zwischen ihnen. Durch welch unglaubliche Zauberei wird dieses Gewirr von Fäden seiner selbst bewusst, fähig, Liebe und Hass zu empfinden, Romane und Sinfonien zu schreiben, Lust und Schmerz zu fühlen und sich aus freiem Willen für Gut oder Böse zu entscheiden? Der australische Philosoph David Chalmers hat die Erklärung des Bewusstseins »das schwere Problem» genannt. Das leichte Problem ist, Unbewusstes wie Atmen, Verdauen, Gehen, Wahrnehmen und tausend andere Dinge zu verstehen. An dem schweren beißen sich Philosophen, Psychologen und Neurowissenschaftler zurzeit bevorzugt die Zähne aus und produzieren tausende Bücher. Ein aktuelles stammt von Douglas R. Hofstadter, Professor für Kognitionswissenschaft an der Universität von Indiana in Bloomington, der vor allem durch sein preisgekröntes Buch »Gödel, Escher, Bach» bekannt geworden ist. Sein neues Werk, so genial und provokant wie seine Vorgänger, ist eine bunte Mischung aus Spekulationen und Geschichten aus seinem Leben. Ein ganzes Kapitel ist einer persönlichen Tragödie gewidmet, die Hofstadter bis heute zu verarbeiten versucht: Im Dezember 1993 starb seine Frau Carol im Alter von 42 Jahren plötzlich an einem Hirntumor. In der Vorstellung von einem Leben nach dem Tod kann er keinen Trost finden; so bleibt ihm nur die Gewissheit, dass Carol in den Erinnerungen derer, die sie kannten und liebten, weiterleben wird - zumindest für eine gewisse Zeit.
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.