000 | 03540nam a22006615i 4500 | ||
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001 | 978-981-33-6137-9 | ||
003 | DE-He213 | ||
005 | 20240423125104.0 | ||
007 | cr nn 008mamaa | ||
008 | 210308s2021 si | s |||| 0|eng d | ||
020 |
_a9789813361379 _9978-981-33-6137-9 |
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024 | 7 |
_a10.1007/978-981-33-6137-9 _2doi |
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050 | 4 | _aTK7895.E42 | |
050 | 4 | _aTK5105.8857 | |
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_aTJF _2bicssc |
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_aTJF _2thema |
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_aGPFC _2thema |
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_a621.38 _223 |
245 | 1 | 0 |
_aFintech with Artificial Intelligence, Big Data, and Blockchain _h[electronic resource] / _cedited by Paul Moon Sub Choi, Seth H. Huang. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2021. |
|
300 |
_aVI, 304 p. 66 illus., 49 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aBlockchain Technologies, _x2661-8346 |
|
505 | 0 | _a1. Blockchain, Cryptocurrency, and Artificial Intelligence in Finance -- 2. Alternative Data, Big Data, and Applications to Finance -- 3. Application of Big Data with Financial Technology in Financial Services -- 4. Using Machine Learning to Predict the Defaults of Credit Card Clients -- 5. Artificial Intelligence and Advanced Time Series Classification: Residual Attention Net for Cross-Domain Modeling -- 6. Generating Synthetic Sequential Data for Enhanced Model Training Through Attention: A Generative Adversarial Net Framework. | |
520 | _aThis book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths. | ||
650 | 0 | _aCooperating objects (Computer systems). | |
650 | 0 |
_aSocial sciences _xMathematics. |
|
650 | 0 | _aBlockchains (Databases). | |
650 | 0 | _aInternet of things. | |
650 | 0 | _aBig data. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aCyber-Physical Systems. |
650 | 2 | 4 | _aMathematics in Business, Economics and Finance. |
650 | 2 | 4 | _aBlockchain. |
650 | 2 | 4 | _aInternet of Things. |
650 | 2 | 4 | _aBig Data. |
650 | 2 | 4 | _aComputational Intelligence. |
700 | 1 |
_aChoi, Paul Moon Sub. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aHuang, Seth H. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789813361362 |
776 | 0 | 8 |
_iPrinted edition: _z9789813361386 |
776 | 0 | 8 |
_iPrinted edition: _z9789813361393 |
830 | 0 |
_aBlockchain Technologies, _x2661-8346 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-33-6137-9 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c174102 _d174102 |