Search (13 results, page 1 of 1)

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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

LCSH

Data mining ; Information retrieval
Data mining / Congresses (GBV)

RVK

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

Subject

Data mining ; Information retrieval
Data mining / Congresses (GBV)

Theme

Data Mining

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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."

LCSH

Data mining

RSWK

Visualisierung / Computergraphik / Data Mining
Data Mining / Visualisierung / Aufsatzsammlung (BVB)

Series

Morgan Kaufmann series in data management systems

Subject

Visualisierung / Computergraphik / Data Mining
Data Mining / Visualisierung / Aufsatzsammlung (BVB)
Data mining

Theme

Data Mining

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Abstract

Das Handbuch der Künstlichen Intelligenz bietet die umfassendste deutschsprachige Übersicht über die Disziplin "Künstliche Intelligenz". Es vereinigt einführende und weiterführende Beiträge u.a. zu folgenden Themen: - Kognition - Neuronale Netze - Suche, Constraints - Wissensrepräsentation - Logik und automatisches Beweisen - Unsicheres und vages Wissen - Wissen über Raum und Zeit - Fallbasiertes Schließen und modellbasierte Systeme - Planen - Maschinelles Lernen und Data Mining - Sprachverarbeitung - Bildverstehen - Robotik - Software-Agenten Das Handbuch bietet eine moderne Einführung in die Künstliche Intelligenz und zugleich einen aktuellen Überblick über Theorien, Methoden und Anwendungen.

Date

21. 3.2008 19:10:22

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Abstract

The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.

Content

Inhalt: Introduction - Principles ofLinked Data - The Web ofData - Linked Data Design Considerations - Linked Data Design Considerations - Consuming Linked Data - Summary and Outlook Vgl.: http://linkeddatabook.com/book.

RSWK

Linked Data

Subject

Linked Data

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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.

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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.

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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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.

LCSH

Data mining
Data Mining and Knowledge Discovery

RSWK

Semantic Web / Metadatenmodell / Data Mining / Ontologie <Wissensverarbeitung> / Kongress / Pusan <2007> (BVB)

Subject

Data mining
Data Mining and Knowledge Discovery
Semantic Web / Metadatenmodell / Data Mining / Ontologie <Wissensverarbeitung> / Kongress / Pusan <2007> (BVB)

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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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Series

Advanced information and knowledge processing

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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.

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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.

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Abstract

Dieses Buch präsentiert ein breites Spektrum aktueller Methoden zur Repräsentation und Verarbeitung (un)sicheren Wissens in maschinellen Systemen in didaktisch aufbereiteter Form. Neben symbolischen Ansätzen des nichtmonotonen Schließens (Default-Logik, hier konstruktiv und leicht verständlich mittels sog. Default-Bäume realisiert) werden auch ausführlich quantitative Methoden wie z.B. probabilistische Markov- und Bayes-Netze vorgestellt. Weitere Abschnitte beschäftigen sich mit Wissensdynamik (Truth Maintenance-Systeme), Aktionen und Planen, maschinellem Lernen, Data Mining und fallbasiertem Schließen.In einem vertieften Querschnitt werden zentrale alternative Ansätze einer logikbasierten Wissensmodellierung ausführlich behandelt. Detailliert beschriebene Algorithmen geben dem Praktiker nützliche Hinweise zur Anwendung der vorgestellten Ansätze an die Hand, während fundiertes Hintergrundwissen ein tieferes Verständnis für die Besonderheiten der einzelnen Methoden vermittelt . Mit einer weitgehend vollständigen Darstellung des Stoffes und zahlreichen, in den Text integrierten Aufgaben ist das Buch für ein Selbststudium konzipiert, eignet sich aber gleichermaßen für eine entsprechende Vorlesung. Im Online-Service zu diesem Buch werden u.a. ausführliche Lösungshinweise zu allen Aufgaben des Buches angeboten.Zahlreiche Beispiele mit medizinischem, biologischem, wirtschaftlichem und technischem Hintergrund illustrieren konkrete Anwendungsszenarien. Von namhaften Professoren empfohlen: State-of-the-Art bietet das Buch zu diesem klassischen Bereich der Informatik. Die wesentlichen Methoden wissensbasierter Systeme werden verständlich und anschaulich dargestellt. Repräsentation und Verarbeitung sicheren und unsicheren Wissens in maschinellen Systemen stehen dabei im Mittelpunkt. In der vierten, verbesserten Auflage wurde die Anzahl der motivierenden Selbsttestaufgaben mit aktuellem Praxisbezug nochmals erweitert. Ein Online-Service mit ausführlichen Musterlösungen erleichtert das Lernen.

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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.