Search (18 results, page 1 of 1)

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Abstract

This book constitutes the refereed proceedings of the joint 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007, held in Busan, Korea, in November 2007. The 50 revised full academic papers and 12 revised application papers presented together with 5 Semantic Web Challenge papers and 12 selected doctoral consortium articles were carefully reviewed and selected from a total of 257 submitted papers to the academic track and 29 to the applications track. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web. Short descriptions of the top five winning applications submitted to the Semantic Web Challenge competition conclude the volume.

Classification

SS 4800 Informatik / Enzyklopädien und Handbücher. Kongreßberichte Schriftenreihe. Tafeln und Formelsammlungen / Schriftenreihen (indiv. Sign.) / Lecture notes in computer science

LCSH

Knowledge management / Congresses
Computer Science

RVK

SS 4800 Informatik / Enzyklopädien und Handbücher. Kongreßberichte Schriftenreihe. Tafeln und Formelsammlungen / Schriftenreihen (indiv. Sign.) / Lecture notes in computer science

Series

Lecture notes in computer science ; 4825

Subject

Knowledge management / Congresses
Computer Science

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Date

23. 3.2008 19:10:22

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.
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."

Series

Morgan Kaufmann series in data management systems

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Abstract

It may seem a strange match - AI and crop irrigation or AI and the Serengeti lions but researchers in artificial intelligence envision expert systems as a new technology for capturing the knowledge and reasoning process of experts in agriculture, wildlife management and many other fields. These computer programmes have a relevance for developing nations that desire to close the gap between themselves and the richer nations of the world. Despite the value and appeal of expert systems for economic and technological development, Schoenhoff dicloses how this technology reflects the Western preoccupation with literacy and rationality. When expert systems are introduced into developing nations, they must interact with persons who reason and articulate their knowledge in ways unfamiliar to high-tech cultures. Knowledge, particularly in poor and traditional communities, may be expressed in proverbs rather than propositions or in folklore rather that formulas. Drawing upon diverse disciplines, the author explores whether such indigenous knowledge can be incorporated into the formal language and artificial rationality of the computer - and the imperative for working toward this incorporation.

LCSH

Expert systems (Computer science)

Series

Contributions to the study of computer science; no.3

Subject

Expert systems (Computer science)

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Abstract

Das Buch präsentiert die vielfältigen Möglichkeiten von Open-Source-Software zur Unterstützung von Wissensmanagement. Der Autor erläutert die Grundlagen und Einsatzmöglichkeiten von Open-Source-Software beim Knowledge Management und entwickelt auf Grund von Analysen konkreter Open-Source-Produkte Entscheidungskriterien und Anleitungen für die Verbesserung von Knowledge Management- und Open-Source-Software. Kosteneinsparungen und Effizienz finden dabei besondere Beachtung.

Content

Inhalt: Definitionen von Knowledge, Knowledge Management und Open Source.- Vision eines Knowledge Management- (KM-) Systems.- Vorhandene Open-Source-Basis.- Technische Basis.- Start mit einem Groupware System.- Alternativ Start mit einem Content-Management-System.- Einbinden von Groupware oder CMS bzw. Erweitern um DMS.- Weiterer Ausbau.- Zusammenfassungen, Abschluss und Ausblick.- Literaturverzeichnis.- Index.

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Abstract

Ontologies have been developed and investigated for quite a while now in artificial intelligente and natural language processing to facilitate knowledge sharing and reuse. More recently, the notion of ontologies has attracied attention from fields such as intelligent information integration, cooperative information systems, information retrieval, electronic commerce, and knowledge management. The author systematicaliy introduces the notion of ontologies to the non-expert reader and demonstrates in detail how to apply this conceptual framework for improved intranet retrieval of corporate information and knowledge and for enhanced Internet-based electronic commerce. In the second part of the book, the author presents a more technical view an emerging Web standards, like XML, RDF, XSL-T, or XQL, allowing for structural and semantic modeling and description of data and information.

LCSH

Database management

Subject

Database management

Theme

Information Resources Management

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Series

Advances in information systems and management science; 39

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Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

Footnote

The final part of the book discusses research in multimedia content management systems and the semantic web, and presents examples and applications for semantic multimedia analysis in search and retrieval systems. These chapters describe example systems in which current projects have been implemented, and include extensive results and real demonstrations. For example, real case scenarios such as ECommerce medical applications and Web services have been introduced. Topics in natural language, speech and image processing techniques and their application for multimedia indexing, and content-based retrieval have been elaborated upon with extensive examples and deployment methods. The editors of the book themselves provide the readers with a chapter about their latest research results on knowledge-based multimedia content indexing and retrieval. Some interesting applications for multimedia content and the semantic web are introduced. Applications that have taken advantage of the metadata provided by MPEG7 in order to realize advance-access services for multimedia content have been provided. The applications discussed in the third part of the book provide useful guidance to researchers and practitioners properly planning to implement semantic multimedia analysis techniques in new research and development projects in both academia and industry. A fourth part should be added to this book: performance measurements for integrated approaches of multimedia analysis and the semantic web. Performance of the semantic approach is a very sophisticated issue and requires extensive elaboration and effort. Measuring the semantic search is an ongoing research area; several chapters concerning performance measurement and analysis would be required to adequately cover this area and introduce it to readers."

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Abstract

Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.

Classification

ST 270 Informatik / Monographien / Software und -entwicklung / Datenbanken, Datenbanksysteme, Data base management, Informationssysteme

RVK

ST 270 Informatik / Monographien / Software und -entwicklung / Datenbanken, Datenbanksysteme, Data base management, Informationssysteme

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LCSH

Knowledge management

Subject

Knowledge management

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Abstract

Thematisch haben die beiden Herausgeber ihre Beitragssammlung in vier Bereiche aufgeteilt: zuerst der Einstieg ins Thema Web 2.0 mit sechs Beiträgen - die Konvergenz von Semantic Web und Web 2.0, Auswirkungen auf die Gesellschaft, Technologien und jeweils die entsprechenden Perspektiven; gute, faktenbasierte Überblicke, die das Buch auf eine solide Grundlage stellen und reichhaltiges Wissen für ansonsten meist oberflächlich geführte Diskussionen zum Thema liefern. Der zweite Themenbereich ist dann den Technologien und Methodem gewidmet: Wie sieht die Technik hinter der "Semantik" im Web aus? Wissensmodellierung, Beispiele wie die Expertensuche, Content Management Systeme oder semantische Wikis. In Teil drei werfen die Autoren dann einen Blick auf bestehende Anwendungen im aktuellen Social Semantic Web und geben einen Ausblick auf deren zukünftige Entwicklungen. Im abschließenden Teil vier schließlich geben die Autoren der drei Beiträge einen Überblick zum "Social Semantic Web" aus sozialwissenschaftlicher Perspektive. Zusammenfassungen am Anfang jedes Beitrags, gute Strukturen zusätzliche Quellen und auch die gut lesbare Länge der Beiträge - angenehme verständlich und konsumierbar. Blumauer und Pellegrini haben auch mit Social Semantic Web: Web 2.0 - Was nun? ganze Arbeit geleistet und ein breites Spektrum an Perspektiven, Meinungen und Quellen zusammengetragen - das Ergebnis ist stellenweise durchaus heterogen und nicht jeder Beitrag muss gefallen, doch das Gesamtergebnis stellt die von den Herausgebern thematisierte heterogene Welt des Social Semantic Web realistisch dar. Wer in Zukunft nicht nur "gefährliches Halbwissen" um das Web 2.0 und das Semantic Web von sich geben will, sollte Social Semantic Web: Web 2.0 - Was nun? gelesen haben!

Content

Semantische Content Management Systeme - Erich Gams und Daniel Mitterdorfer Tag-Recommender gestützte Annotation von Web-Dokumenten - Andreas Blumauer und Martin Hochmeister Semantische Wikis - Sebastian Schaffert, François Bry, Joachim Baumeister und Malte Kiesel Semantische Mashups auf Basis Vernetzter Daten - Sören Auer, Jens Lehmann und Christian Bizer Web-gestütztes Social Networking am Beispiel der "Plattform Wissensmanagement" - Stefanie N. Lindstaedt und Claudia Thurner Explorative Netzwerkanalyse im Living Web - Gernot Tscherteu und Christian Langreiter Semantic Desktop - Leo Sauermann, Malte Kiesel, Kinga Schumacher und Ansgar Bernardi Social Bookmarking am Beispiel BibSonomy - Andreas Hotho, Robert Jäschke, Dominik Benz, Miranda Grahl, Beate Krause, Christoph Schmitz und Gerd Stumme Semantic Wikipedia - Markus Krötzsch und Denny Vrandecic Die Zeitung der Zukunft - Christoph Wieser und Sebastian Schaffert Das Semantic Web als Werkzeug in der biomedizinischen Forschung - Holger Stenzhorn und Matthias Samwald

Footnote

Vgl.: http://www.springer.com/computer/database+management+%26+information+retrieval/book/978-3-540-72215-1.

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Date

21. 3.2008 19:10:22

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LCSH

Wikis (Computer science)

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Wikis (Computer science)

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Expert systems (Computer science)

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Expert systems (Computer science)

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Computer science

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Computer science

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Lecture notes in computer science; 6497

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Imprint

Hershey, Pa. : Information Science Reference

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Lecture notes in computer science; 6496

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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.