| 000 | 07018nam a2200697 i 4500 | ||
|---|---|---|---|
| 001 | 7376425 | ||
| 003 | IEEE | ||
| 005 | 20200413152919.0 | ||
| 006 | m eo d | ||
| 007 | cr cn |||m|||a | ||
| 008 | 151229s2016 caua foab 000 0 eng d | ||
| 020 |
_a9781627057721 _qebook |
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| 020 |
_z9781627057714 _qprint |
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| 024 | 7 |
_a10.2200/S00676ED1V01Y201509DTM042 _2doi |
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| 035 | _a(CaBNVSL)swl00406020 | ||
| 035 | _a(OCoLC)933561490 | ||
| 040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aQA76.9.A43 _bB478 2016 |
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| 082 | 0 | 4 |
_a005.1 _223 |
| 100 | 1 |
_aBerti-Équille, Laure., _eauthor. |
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| 245 | 1 | 0 |
_aVeracity of data : _b from truth discovery computation algorithms to models of misinformation dynamics / _cLaure Berti-Équille and Javier Borge-Holthoefer. |
| 264 | 1 |
_aSan Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool, _c2016. |
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| 300 |
_a1 PDF (xiii, 141 pages) : _billustrations. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_aelectronic _2isbdmedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 490 | 1 |
_aSynthesis lectures on data management, _x2153-5426 ; _v# 42 |
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| 538 | _aMode of access: World Wide Web. | ||
| 538 | _aSystem requirements: Adobe Acrobat Reader. | ||
| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 504 | _aIncludes bibliographical references (pages 115-139). | ||
| 505 | 0 | _a1. 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 -- | |
| 505 | 8 | _a2. Information extraction -- 2.1 Introduction -- 2.2 Information extraction pipeline -- 2.2.1 Tokenization and sentence segmentation -- 2.2.2 Normalization -- 2.2.3 Part-of-speech tagging -- 2.2.4 Named entity recognition -- 2.2.5 Mention detection and coreference resolution -- 2.3 Knowledge graph population -- 2.3.1 Entity discovery and linking -- 2.3.2 Relation extraction and inference -- 2.3.3 Slot filling -- 2.3.4 Slot filler validation -- 2.4 Contradiction detection -- 2.5 Conclusion -- | |
| 505 | 8 | _a3. Truth discovery computation -- 3.1 Introduction -- 3.2 Terminology -- 3.2.1 Notations and basic principle -- 3.2.2 Characterization of truth discovery methods -- 3.2.3 Modeling assumptions -- 3.3 Truth discovery methods -- 3.3.1 Agreement-based methods -- 3.3.2 MAP estimation-based methods -- 3.3.3 Analytical methods -- 3.3.4 Bayesian inference-based methods -- 3.4 New developments -- 3.4.1 Evolving truth discovery -- 3.4.2 Zero-to-many truth -- 3.4.3 Long-tail phenomenon -- 3.4.4 Truth discovery from crowdsourced data -- 3.5 Conclusion -- | |
| 505 | 8 | _a4. Trust computation -- 4.1 Introduction -- 4.2 Definitions -- 4.3 Probabilistic trust computation -- 4.3.1 Direct trust models -- 4.3.2 Combining direct and indirect trust models -- 4.3.3 Evaluation of trust computing schemes -- 4.4 Trust propagation -- 4.4.1 Overriding trust propagation -- 4.4.2 Aggregation-based propagation -- 4.5 Conclusion -- | |
| 505 | 8 | _a5. Misinformation dynamics -- 5.1 Introduction -- 5.2 Theoretical foundations -- 5.2.1 Terminology in complex networks -- 5.2.2 Complex network descriptors -- 5.2.3 Network models -- 5.3 Disease and rumor propagation models -- 5.3.1 Epidemic spreading -- 5.3.2 Rumor propagation -- 5.3.3 Misinformation dynamics -- 5.4 Theory under test: empirical feedback -- 5.4.1 Source identification -- 5.4.2 Dynamical role of source and intermediate nodes -- 5.5 Misinformation containment and meme mutation in complex social systems -- 5.5.1 Influence limitation: averting malicious viral processes -- 5.5.2 Information mutation: meme tracking -- | |
| 505 | 8 | _a6. Transdisciplinary challenges of truth discovery -- 6.1 Introduction -- 6.2 From information to data -- 6.2.1 Big data vs. sparse facts -- 6.2.2 Decontextualization -- 6.2.3 Uncertain, incomplete, and biased observations -- 6.2.4 Data and information fusion across languages, modalities, and media -- 6.3 From multisource data to networks of sources and networks of content -- 6.3.1 Truth discovery in common multiplexes -- 6.3.2 Time-dependent truth discovery -- 6.3.3 Complex interconnected networks of sources and multimedia content -- 6.4 Final remark -- Bibliography -- Authors' biographies. | |
| 506 | 1 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | |
| 510 | 0 | _aCompendex | |
| 510 | 0 | _aINSPEC | |
| 510 | 0 | _aGoogle scholar | |
| 510 | 0 | _aGoogle book search | |
| 520 | 3 | _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. | |
| 530 | _aAlso available in print. | ||
| 588 | _aTitle from PDF title page (viewed on December 29, 2015). | ||
| 650 | 0 |
_aVerification (Logic) _xComputer programs. |
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| 650 | 0 | _aComputer algorithms. | |
| 650 | 0 |
_aDatabases _xEvaluation. |
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| 650 | 0 | _aData editing. | |
| 650 | 0 | _aData integrity. | |
| 653 | _ainformation extraction | ||
| 653 | _atruth discovery | ||
| 653 | _adata veracity | ||
| 653 | _atrust computation | ||
| 653 | _amisinformation dynamics | ||
| 700 | 1 |
_aBorge-Holthoefer, Javier., _eauthor. |
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| 776 | 0 | 8 |
_iPrint version: _z9781627057714 |
| 830 | 0 | _aSynthesis digital library of engineering and computer science. | |
| 830 | 0 |
_aSynthesis lectures on data management ; _v# 42. _x2153-5426 |
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| 856 | 4 | 2 |
_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=7376425 |
| 999 |
_c562176 _d562176 |
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