Search (9 results, page 1 of 1)

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Abstract

Unternehmen sehen sich heutzutage regelmäßig der Herausforderung gegenübergestellt, aus umfangreichen Mengen an Dokumenten schnell relevante Informationen zu identifizieren. Dabei zeigt sich jedoch, dass Suchverfahren, die lediglich syntaktische Abgleiche von Informationsbedarfen mit potenziell relevanten Dokumenten durchführen, häufig nicht die an sie gestellten Erwartungen erfüllen. Viel versprechendes Potenzial bietet hier der Einsatz von Ontologien für das Information Retrieval. Beim ontologiebasierten Information Retrieval werden Ontologien eingesetzt, um Wissen in einer Form abzubilden, die durch Informationssysteme verarbeitet werden kann. Eine Berücksichtigung des so explizierten Wissens durch Suchalgorithmen führt dann zu einer optimierten Deckung von Informationsbedarfen. Jan Hermans stellt in seinem Buch ein adaptives Referenzmodell für die Entwicklung von ontologiebasierten Information Retrieval-Systemen vor. Zentrales Element seines Modells ist die einsatzkontextspezifische Adaption des Retrievalprozesses durch bewährte Techniken, die ausgewählte Aspekte des ontologiebasierten Information Retrievals bereits effektiv und effizient unterstützen. Die Anwendung des Referenzmodells wird anhand eines Fallbeispiels illustriert, bei dem ein Information Retrieval-System für die Suche nach Open Source-Komponenten entwickelt wird. Das Buch richtet sich gleichermaßen an Dozenten und Studierende der Wirtschaftsinformatik, Informatik und Betriebswirtschaftslehre sowie an Praktiker, die die Informationssuche im Unternehmen verbessern möchten. Jan Hermans, Jahrgang 1978, studierte Wirtschaftsinformatik an der Westfälischen Wilhelms-Universität in Münster. Seit 2003 war er als Wissenschaftlicher Mitarbeiter am European Research Center for Information Systems der WWU Münster tätig. Seine Forschungsschwerpunkte lagen in den Bereichen Wissensmanagement und Information Retrieval. Im Mai 2008 erfolgte seine Promotion zum Doktor der Wirtschaftswissenschaften.

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

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.
Semantic web technologies are explained, and ontology representation is emphasized. There is an excellent summary of the fundamental theory behind applying a knowledge-engineering approach to vision problems. This summary represents the concept of the semantic web and multimedia content analysis. A definition of the fuzzy knowledge representation that can be used for realization in multimedia content applications has been provided, with a comprehensive analysis. The second part of the book introduces the multimedia content analysis approaches and applications. In addition, some examples of methods applicable to multimedia content analysis are presented. Multimedia content analysis is a very diverse field and concerns many other research fields at the same time; this creates strong diversity issues, as everything from low-level features (e.g., colors, DCT coefficients, motion vectors, etc.) up to the very high and semantic level (e.g., Object, Events, Tracks, etc.) are involved. The second part includes topics on structure identification (e.g., shot detection for video sequences), and object-based video indexing. These conventional analysis methods are supplemented by results on semantic multimedia analysis, including three detailed chapters on the development and use of knowledge models for automatic multimedia analysis. Starting from object-based indexing and continuing with machine learning, these three chapters are very logically organized. Because of the diversity of this research field, including several chapters of recent research results is not sufficient to cover the state of the art of multimedia. The editors of the book should write an introductory chapter about multimedia content analysis approaches, basic problems, and technical issues and challenges, and try to survey the state of the art of the field and thus introduce the field to the reader.
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

Das Semantic Web bezeichnet ein erweitertes World Wide Web (WWW), das die Bedeutung von präsentierten Inhalten in neuen standardisierten Sprachen wie RDF Schema und OWL modelliert. Diese Arbeit befasst sich mit dem Aspekt des Information Retrieval, d.h. es wird untersucht, in wie weit Methoden der Informationssuche sich auf modelliertes Wissen übertragen lassen. Die kennzeichnenden Merkmale von IR-Systemen wie vage Anfragen sowie die Unterstützung unsicheren Wissens werden im Kontext des Semantic Web behandelt. Im Fokus steht die Suche nach Fakten innerhalb einer Wissensdomäne, die entweder explizit modelliert sind oder implizit durch die Anwendung von Inferenz abgeleitet werden können. Aufbauend auf der an der Universität Duisburg-Essen entwickelten Retrievalmaschine PIRE wird die Anwendung unsicherer Inferenz mit probabilistischer Prädikatenlogik (pDatalog) implementiert.

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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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Abstract

Das wachsende Informationsvolumen im WWW führt paradoxerweise zu einer immer schwierigeren Nutzung, das Finden und Verknüpfen von Informationen in einem unstrukturierten Umfeld wird zur Sisyphosarbeit. Hier versprechen Semantic-Web-Ansätze Abhilfe. Die Autoren beschreiben Technologien, wie eine semantische Integration verteilter Daten durch verteilte Ontologien erreicht werden kann. Diese Techniken sind sowohl für Forscher als auch für Professionals interessant, die z.B. die Integration von Produktdaten aus verteilten Datenbanken im WWW oder von lose miteinander verbunden Anwendungen in verteilten Organisationen implementieren sollen.

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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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Content

Inhalt: What is social software? -- Blogs -- Blogs in libraries : practical applications -- RSS -- Wikis -- Online communities -- Social networking -- Social bookmarking and collaborative filtering -- Tools for synchronous online reference -- The mobile revolution -- Podcasting -- Screencasting and vodcasting -- Gaming -- What will work @ your library -- Keeping up : a primer -- Future trends in social software.

Footnote

Rez. in: JASIST 59(1008) no.11, S.1866 (L.E. Harris)

LCSH

Telecommunication in libraries

Subject

Telecommunication in libraries

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Abstract

Libraries have always been an inspiration for the standards and technologies developed by semantic web activities. However, except for the Dublin Core specification, semantic web and social networking technologies have not been widely adopted and further developed by major digital library initiatives and projects. Yet semantic technologies offer a new level of flexibility, interoperability, and relationships for digital repositories. Kruk and McDaniel present semantic web-related aspects of current digital library activities, and introduce their functionality; they show examples ranging from general architectural descriptions to detailed usages of specific ontologies, and thus stimulate the awareness of researchers, engineers, and potential users of those technologies. Their presentation is completed by chapters on existing prototype systems such as JeromeDL, BRICKS, and Greenstone, as well as a look into the possible future of semantic digital libraries. This book is aimed at researchers and graduate students in areas like digital libraries, the semantic web, social networks, and information retrieval. This audience will benefit from detailed descriptions of both today's possibilities and also the shortcomings of applying semantic web technologies to large digital repositories of often unstructured data.

Content

Inhalt: Introduction to Digital Libraries and Semantic Web: Introduction / Bill McDaniel and Sebastian Ryszard Kruk - Digital Libraries and Knowledge Organization / Dagobert Soergel - Semantic Web and Ontologies / Marcin Synak, Maciej Dabrowski and Sebastian Ryszard Kruk - Social Semantic Information Spaces / John G. Breslin A Vision of Semantic Digital Libraries: Goals of Semantic Digital Libraries / Sebastian Ryszard Kruk and Bill McDaniel - Architecture of Semantic Digital Libraries / Sebastian Ryszard Kruk, Adam Westerki and Ewelina Kruk - Long-time Preservation / Markus Reis Ontologies for Semantic Digital Libraries: Bibliographic Ontology / Maciej Dabrowski, Macin Synak and Sebastian Ryszard Kruk - Community-aware Ontologies / Slawomir Grzonkowski, Sebastian Ryszard Kruk, Adam Gzella, Jakub Demczuk and Bill McDaniel Prototypes of Semantic Digital Libraries: JeromeDL: The Social Semantic Digital Library / Sebastian Ryszard Kruk, Mariusz Cygan, Adam Gzella, Tomasz Woroniecki and Maciej Dabrowski - The BRICKS Digital Library Infrastructure / Bernhard Haslhofer and Predrag Knezevié - Semantics in Greenstone / Annika Hinze, George Buchanan, David Bainbridge and Ian Witten Building the Future - Semantic Digital Libraries in Use: Hyperbooks / Gilles Falquet, Luka Nerima and Jean-Claude Ziswiler - Semantic Digital Libraries for Archiving / Bill McDaniel - Evaluation of Semantic and Social Technologies for Digital Libraries / Sebastian Ryszard Kruk, Ewelina Kruk and Katarzyna Stankiewicz - Conclusions: The Future of Semantic Digital Libraries / Sebastian Ryszard Kruk and Bill McDaniel

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Abstract

As the World Wide Web continues to expand, it becomes increasingly difficult for users to obtain information efficiently. Because most search engines read format languages such as HTML or SGML, search results reflect formatting tags more than actual page content, which is expressed in natural language. Spinning the Semantic Web describes an exciting new type of hierarchy and standardization that will replace the current "Web of links" with a "Web of meaning." Using a flexible set of languages and tools, the Semantic Web will make all available information - display elements, metadata, services, images, and especially content - accessible. The result will be an immense repository of information accessible for a wide range of new applications. This first handbook for the Semantic Web covers, among other topics, software agents that can negotiate and collect information, markup languages that can tag many more types of information in a document, and knowledge systems that enable machines to read Web pages and determine their reliability. The truly interdisciplinary Semantic Web combines aspects of artificial intelligence, markup languages, natural language processing, information retrieval, knowledge representation, intelligent agents, and databases.