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007			cr nn 008mamaa
008			220601s2016 sz | s |||| 0|eng d
020			_a9783031018558
024	7		_a10.1007/978-3-031-01855-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.A43 _b2016 EB
100	1		_aBerti-Équille, Laure _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686166
245	1	0	_aVeracity of Data _cby Laure Berti-Équille, Javier Borge-Holthoefer
250			_a1st edition 2016
264		1	_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XIII, 141 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Data Management _x2153-5426
505	0		_aIntroduction to Data Veracity -- Information Extraction -- Truth Discovery Computation -- Trust Computation -- Misinformation Dynamics -- Transdisciplinary Challenges of Truth Discovery -- Bibliography -- Authors' Biographies.
520			_aOn 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.
988			_aSynthesis Collection of Technology_2016
650		7	_2embne _9151819 _aAlgoritmos computacionales
650		7	_2embne _9138966 _aBases de datos _xEvaluación
700	1		_aBorge-Holthoefer, Javier _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686167
776	0	8	_iPrinted edition: _z9783031007279
776	0	8	_iPrinted edition: _z9783031029837
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01855-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _esc _zSI