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  • 1
    UID:
    b3kat_BV046427515
    Format: 1 Online-Resource (xiii, 141 Seiten) , Illustrationen
    ISBN: 9781627057721
    Series Statement: Synthesis lectures on data management #42
    Content: On the Web, a massive amount of user-generated content is available through various channels (e.g., texts, tweets, Web tables, databases, multimedia-sharing platforms, etc.). Conflicting information, rumors, erroneous and fake content can be easily spread across multiple sources, making it hard to distinguish between what is true and what is not. This book gives an overview of fundamental issues and recent contributions for ascertaining the veracity of data in the era of Big Data. The text is organized into six chapters, focusing on structured data extracted from texts. Chapter 1 introduces the problem of ascertaining the veracity of data in a multi-source and evolving context. Issues related to information extraction are presented in Chapter 2. Current truth discovery computation algorithms are presented in details in Chapter 3. It is followed by practical techniques for evaluating data source reputation and authoritativeness in Chapter 4. The theoretical foundations and various approaches for modeling diffusion phenomenon of misinformation spreading in networked systems are studied in Chapter 5. Finally, truth discovery computation from extracted data in a dynamic context of misinformation propagation raises interesting challenges that are explored in Chapter 6. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of fact-checking, truth discovery, or rumor spreading
    Note: Part of: Synthesis digital library of engineering and computer science , Title from PDF title page (viewed on December 29, 2015)
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-1-62705-771-4
    Language: English
    Keywords: Data Mining ; Zuverlässigkeit ; Datenqualität
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool
    UID:
    gbv_1656743000
    Format: Online-Ressource (xiii, 141 pages) , illustrations.
    ISBN: 9781627057721
    Series Statement: Synthesis lectures on data management # 42
    Content: On the Web, a massive amount of user-generated content is available through various channels (e.g., texts, tweets, Web tables, databases, multimedia-sharing platforms, etc.). Conflicting information, rumors, erroneous and fake content can be easily spread across multiple sources, making it hard to distinguish between what is true and what is not. This book gives an overview of fundamental issues and recent contributions for ascertaining the veracity of data in the era of Big Data. The text is organized into six chapters, focusing on structured data extracted from texts. Chapter 1 introduces the problem of ascertaining the veracity of data in a multi-source and evolving context. Issues related to information extraction are presented in Chapter 2. Current truth discovery computation algorithms are presented in details in Chapter 3. It is followed by practical techniques for evaluating data source reputation and authoritativeness in Chapter 4. The theoretical foundations and various approaches for modeling diffusion phenomenon of misinformation spreading in networked systems are studied in Chapter 5. Finally, truth discovery computation from extracted data in a dynamic context of misinformation propagation raises interesting challenges that are explored in Chapter 6. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of fact-checking, truth discovery, or rumor spreading.
    Note: Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 115-139). - Compendex. INSPEC. Google scholar. Google book search. - Title from PDF title page (viewed on December 29, 2015) , 1. Introduction to data veracity -- 1.1 The fourth "V" of big data -- 1.2 Main causes affecting data veracity -- 1.3 Classification of truth discovery approaches -- 1.4 Information extraction -- 1.5 Fact-checking and trust computation -- 1.6 Misinformation dynamics in networked systems -- , Mode of access: World Wide Web. , System requirements: Adobe Acrobat Reader.
    Additional Edition: ISBN 9781627057714
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9781627057714
    Language: English
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  • 3
    UID:
    edochu_18452_25906
    Format: 1 Online-Ressource (25 Seiten)
    Content: The analysis of complex networks is devoted to the statistical characterization of the topology of graphs at different scales of organization in order to understand their functionality. While the modular structure of networks has become an essential element to better apprehend their complexity, the efforts to characterize the mesoscale of networks have focused on the identification of the modules rather than describing the mesoscale in an informative manner. Here we propose a framework to characterize the position every node takes within the modular configuration of complex networks and to evaluate their function accordingly. For illustration, we apply this framework to a set of synthetic networks, empirical neural networks, and to the transcriptional regulatory network of the Mycobacterium tuberculosis. We find that the architecture of both neuronal and transcriptional networks are optimized for the processing of multisensory information with the coexistence of well-defined modules of specialized components and the presence of hubs conveying information from and to the distinct functional domains.
    Content: Peer Reviewed
    In: [London] : IOP, 16,12
    Language: English
    URL: Volltext  (kostenfrei)
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