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  • × classification_ss:"54.72 (Künstliche Intelligenz)"
  1. Fuchs, W.R.: Denkmaschinen : mit einem Geleitwort von Professor Dr. Yehoshua Bar-Hillel (1968) 0.03 
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    Abstract
    Ein Buch aus der Anfangszeit der Computer mit vielen Passagen einer semantischen Informationstheorie
    BK
    54.08 (Informatik in Beziehung zu Mensch und Gesellschaft)
    Classification
    54.08 (Informatik in Beziehung zu Mensch und Gesellschaft)
    Footnote
    Weitere Ausgaben. Auch u.d.T.: Knaurs Buch der Denkmaschinen: Informationstheorie u. Kybernetik.
    LCSH
    Elektronische Datenverarbeitung / Informationstheorie
    RSWK
    Datenverarbeitung / Informationstheorie / Kybernetik
    Datenverarbeitung / Wörterbuch
    Subject
    Datenverarbeitung / Informationstheorie / Kybernetik
    Datenverarbeitung / Wörterbuch
    Elektronische Datenverarbeitung / Informationstheorie
  2. Developments in applied artificial intelligence : proceedings / 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, Loughborough, UK, June 23 - 26, 2003 (2003) 0.02 
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    Abstract
    This book constitutes the refereed proceedings of the 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, held in Loughborough, UK in June 2003. The 81 revised full papers presented were carefully reviewed and selected from more than 140 submissions. Among the topics addressed are soft computing, fuzzy logic, diagnosis, knowledge representation, knowledge management, automated reasoning, machine learning, planning and scheduling, evolutionary computation, computer vision, agent systems, algorithmic learning, tutoring systems, financial analysis, etc.
    Series
    Lecture notes in computer science ; Vol. 2718 : Lecture notes in artificial intelligence
  3. Zur Konstruktion künstlicher Gehirne (2009) 0.02 
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    Abstract
    In diesem Buch wird eine erste Generation von künstlichen Hirnen für das Sehen vorgestellt. Auf der ausschließlichen Grundlage von Neuron- und Synapsenmodellen wird ein Objekterkennungssystem konstruiert, welches eine Merkmalspyramide mit 8 Orientierungen und 5 Auflösungsskalen für 1000 Objekte sowie die Netze für die Bindung von Merkmalen zu Objekten umfasst. Dieses Sehsystem kann unabhängig von der Beleuchtung, dem Gesichtausdruck, der Entfernung und einer Drehung, welche die Objektkomponenten sichtbar lässt, Objekte erkennen. Seine Realisierung erfordert 59 Chips - davon sind 4 verschieden - welche mittels 3D Technologie zu einem Quader von 8mm x 8mm x 1mm aufgeschichtet sind. Die Leistungsfähigkeit des neuronal-synaptischen Netzwerkes beruht auf der Einführung von schnell veränderlichen dynamischen Synapsen. Anders als Netze mit konstanten Synapsen können solche mit dynamischen Synapsen allgemeine Aufgaben der Mustererkennung übernehmen. Die raum-zeitliche Korrelationsstruktur von Mustern wird durch eine einzige synaptische Differentialgleichung in universeller Weise erfasst. Die Korrelation kann in Erscheinung treten als synchrone Pulstätigkeit einer Neurongruppe, wodurch das Vorliegen eines Merkmals in robuster Weise angezeigt wird, oder als Bindung von Merkmalen zu Objekten.
    Auch wenn die Autoren der Überzeugung sind, dass noch viele Generationen folgen müssen, um die Leistungsfähigkeit des menschlichen Gehirns zu erreichen, sehen sie doch ein neues Rechen-Zeitalter aufziehen. Es gab Zeiten, da wurden Computer mit ihrer Präzision, Zuverlässigkeit und rasanten Geschwindigkeit der feuchten Materie unseres Gehirns als so weit überlegen angesehen wie das Düsenflugzeug dem Spatzen. Dass diese Zeiten vorbei sind, ist gewiss, denn durch formale Logik inspirierte, algorithmisch gesteuerte und mit digitaler Elektronik realisierte Systeme, die heutigen Computer, stoßen an ihre Komplexitätsgrenzen. Andererseits eröffnen die hier vorgestellten Ergebnisse den Weg zu einer Alternative. Ein Paradigmenwechsel liegt in der Luft: vom fremdorganisierten zum selbstorganisierten Computer.
    Content
    1. Problematik der Modellierung künstlicher Gehirne - 2. Informationsverarbeitung in Netzen mit konstanten Synapsen - 3. Allgemeine Theorie der Netze mit dynamischen Synapsen - 4. Makrodynamik der Netze mit konstanten Synapsen - 5. Informationsverarbeitung mit dynamischen Synapsen - 6. Netze für die Merkmalsdetektion - 7. Netze für die Merkmalserkennung - 8. Netze für die robuste Kopfdetektion - 9. Ausblick - 10. Vor üb er legungen zur mikroelektronischen Realisierung - 11. Elementare Schaltungen für Neuronen, Synapsen und Photosensoren - 12. Simulation mikroelektronischer neuronaler Schaltungen und Systeme - 13. Architektur und Chip-Entwurf des Merkmalserkenners - 14. Architektur und Chip-Entwurf für Merkmalsdetektoren - 15. 3D-Stapeltechnik für den Sehwürfel - 16. Architektur eines Sehwürfels der ersten Generation Vgl.: https://link.springer.com/book/10.1007%2F978-3-642-00191-8.
    Editor
    Malsburg, C. von der
  4. Lenzen, M.: Künstliche Intelligenz : was sie kann & was uns erwartet (2018) 0.02 
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    Abstract
    Künstliche Intelligenz (KI) steht für Maschinen, die können, was der Mensch kann: hören und sehen, sprechen, lernen, Probleme lösen. In manchem sind sie inzwischen nicht nur schneller, sondern auch besser als der Mensch. Wie funktionieren diese klugen Maschinen? Bedrohen sie uns, machen sie uns gar überflüssig? Die Journalistin und KI-Expertin Manuela Lenzen erklärt anschaulich, was Künstliche Intelligenz kann und was uns erwartet. Künstliche Intelligenz ist das neue Zauberwort des digitalen Kapitalismus. Intelligente Computersysteme stellen medizinische Diagnosen und geben Rechtsberatung. Sie managen den Aktienhandel und steuern bald unsere Autos. Sie malen, dichten, dolmetschen und komponieren. Immer klügere Roboter stehen an den Fließbändern, begrüßen uns im Hotel, führen uns durchs Museum oder braten Burger und schnipseln den Salat dazu. Doch neben die Utopie einer schönen neuen intelligenten Technikwelt sind längst Schreckbilder getreten: von künstlichen Intelligenzen, die uns auf Schritt und Tritt überwachen, die unsere Arbeitsplätze übernehmen und sich unserer Kontrolle entziehen. Manuela Lenzen zeigt, welche Hoffnungen und Befürchtungen realistisch sind und welche in die Science Fiction gehören. Sie beschreibt, wie ein gutes Leben mit der Künstlichen Intelligenz aussehen könnte - und dass wir von klugen Maschinen eine Menge über uns selbst lernen können.
    Date
    18. 6.2018 19:22:02
  5. Klaus, G.; Liebscher, H.: Systeme - Informationen - Strategien : eine Einführung in die kybernetischen Grundgedanken der System- und Regelungstheorie, Informationstheorie und Spieltheorie (1974) 0.01 
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  6. Allman, W.F.: Menschliches Denken - Künstliche Intelligenz : von der Gehirnforschung zur nächsten Computer-Generation (1990) 0.01 
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    Content
    Enthält die Kapitel: (E) Vom Neuron zur Psyche; (1) Das Rüstzeug des Geistes: die Revolution der neuen Konnektionisten: (2) Das Puzzlespiel: die Mechanismen des Denkens; (3) Die große Wasserscheide: Gehirnforschung contra Geistesforschung; (4) Wetware: die Anatomie des Erinnerungsvermögens; (5) Wodurch wird ein Neuronenbündel so schlau?: die Wissenschaft von der Komplexität; (6) Der Computer als Autodidakt: wie Neuralnetzwerke das Laufen lernen; (7) Maschinenträume: Neuralnetzwerke im Arbeitseinsatz; (8) Streitbare Denker: der Kampf um die Herzen der Wissenschaftler; (9) Der Musterschüler: NETalk lernt laut lesen
  7. Keyser, P. de: Indexing : from thesauri to the Semantic Web (2012) 0.00 
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    Abstract
    Indexing consists of both novel and more traditional techniques. Cutting-edge indexing techniques, such as automatic indexing, ontologies, and topic maps, were developed independently of older techniques such as thesauri, but it is now recognized that these older methods also hold expertise. Indexing describes various traditional and novel indexing techniques, giving information professionals and students of library and information sciences a broad and comprehensible introduction to indexing. This title consists of twelve chapters: an Introduction to subject readings and theasauri; Automatic indexing versus manual indexing; Techniques applied in automatic indexing of text material; Automatic indexing of images; The black art of indexing moving images; Automatic indexing of music; Taxonomies and ontologies; Metadata formats and indexing; Tagging; Topic maps; Indexing the web; and The Semantic Web.
    Date
    24. 8.2016 14:03:22
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  8. Helbig, H.: Knowledge representation and the semantics of natural language (2014) 0.00 
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    Abstract
    Natural Language is not only the most important means of communication between human beings, it is also used over historical periods for the preservation of cultural achievements and their transmission from one generation to the other. During the last few decades, the flod of digitalized information has been growing tremendously. This tendency will continue with the globalisation of information societies and with the growing importance of national and international computer networks. This is one reason why the theoretical understanding and the automated treatment of communication processes based on natural language have such a decisive social and economic impact. In this context, the semantic representation of knowledge originally formulated in natural language plays a central part, because it connects all components of natural language processing systems, be they the automatic understanding of natural language (analysis), the rational reasoning over knowledge bases, or the generation of natural language expressions from formal representations. This book presents a method for the semantic representation of natural language expressions (texts, sentences, phrases, etc.) which can be used as a universal knowledge representation paradigm in the human sciences, like linguistics, cognitive psychology, or philosophy of language, as well as in computational linguistics and in artificial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.
    Footnote
    Vgl. auch die anderen Ausgabe in dt. u. engl. Sprache
  9. Sakr, S.; Wylot, M.; Mutharaju, R.; Le-Phuoc, D.; Fundulaki, I.: Linked data : storing, querying, and reasoning (2018) 0.00 
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    Abstract
    This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.
    Footnote
    Rez. in: JASIST 70(2019) no.8, S.905-907 (Dean Allemang).
  10. Pang, B.; Lee, L.: Opinion mining and sentiment analysis (2008) 0.00 
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    Abstract
    An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object. Opinion Mining and Sentiment Analysis covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. The focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. The survey includes an enumeration of the various applications, a look at general challenges and discusses categorization, extraction and summarization. Finally, it moves beyond just the technical issues, devoting significant attention to the broader implications that the development of opinion-oriented information-access services have: questions of privacy, vulnerability to manipulation, and whether or not reviews can have measurable economic impact. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided. Opinion Mining and Sentiment Analysis is the first such comprehensive survey of this vibrant and important research area and will be of interest to anyone with an interest in opinion-oriented information-seeking systems.
    Series
    Foundations and trends(r) in information retrieval; 2,1/2
  11. Stuart, D.: Practical ontologies for information professionals (2016) 0.00 
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    Abstract
    Practical Ontologies for Information Professionals provides an accessible introduction and exploration of ontologies and demonstrates their value to information professionals. More data and information is being created than ever before. Ontologies, formal representations of knowledge with rich semantic relationships, have become increasingly important in the context of today's information overload and data deluge. The publishing and sharing of explicit explanations for a wide variety of conceptualizations, in a machine readable format, has the power to both improve information retrieval and discover new knowledge. Information professionals are key contributors to the development of new, and increasingly useful, ontologies. Practical Ontologies for Information Professionals provides an accessible introduction to the following: defining the concept of ontologies and why they are increasingly important to information professionals ontologies and the semantic web existing ontologies, such as RDF, RDFS, SKOS, and OWL2 adopting and building ontologies, showing how to avoid repetition of work and how to build a simple ontology interrogating ontologies for reuse the future of ontologies and the role of the information professional in their development and use. This book will be useful reading for information professionals in libraries and other cultural heritage institutions who work with digitalization projects, cataloguing and classification and information retrieval. It will also be useful to LIS students who are new to the field.
    Footnote
    Rez. in: Cataloging and classification quarterly 55(2017) no.6, S.413-414 (Christine DeZelar-Tiedman).

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  • m 11
  • s 2

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