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001 | 978-981-19-7369-7 | ||
003 | DE-He213 | ||
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007 | cr nn 008mamaa | ||
008 | 221129s2023 si | s |||| 0|eng d | ||
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_a9789811973697 _9978-981-19-7369-7 |
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024 | 7 |
_a10.1007/978-981-19-7369-7 _2doi |
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072 | 7 |
_aUN _2bicssc |
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_aCOM021000 _2bisacsh |
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_aUN _2thema |
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_a005.7 _223 |
100 | 1 |
_aChen, Bernard. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aWineinformatics _h[electronic resource] : _bA New Data Science Application / _cby Bernard Chen. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2023. |
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300 |
_aIX, 69 p. 1 illus. _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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_atext file _bPDF _2rda |
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490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
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505 | 0 | _aChapter 1 Introduction -- Chapter 2 Data collection and preprocessing -- Chapter 3 Classification in Wineinformatics -- Chapter 4 Regression on Wine Prediction -- Chapter 5 Analysis on Wine Reviewers -- Chapter 6 Advanced Application of the Computational Wine Wheel -- Chapter 7 Conclusion and Future Works. | |
520 | _aWineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and consumers. This book systematically investigates how to process human language format reviews and mine useful knowledge from a large volume of processed data. This book presents a human language processing tool named Computational Wine Wheel to process professional wine reviews and three novel Wineinformatics studies to analyze wine quality, price and reviewers. Through the lens of data science, the author demonstrates how the wine receives 90+ scores out of 100 points from Wine Spectator, how to predict a wine’s specific grade and price through wine reviews and how to rank a group of wine reviewers. The book also shows the advanced application of the Computational Wine Wheel to capture more information hidden in wine reviews and the possibility of extending the wheel to coffee, tea beer, sake and liquors. This book targets computer scientists, data scientists and wine industrial researchers, who are interested in Wineinformatics. Senior data science undergraduate and graduate students may also benefit from this book. | ||
650 | 0 |
_aArtificial intelligence _xData processing. |
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650 | 0 | _aMachine learning. | |
650 | 0 | _aNatural language processing (Computer science). | |
650 | 0 | _aExpert systems (Computer science). | |
650 | 0 | _aBusiness information services. | |
650 | 0 |
_aSocial sciences _xData processing. |
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650 | 1 | 4 | _aData Science. |
650 | 2 | 4 | _aMachine Learning. |
650 | 2 | 4 | _aNatural Language Processing (NLP). |
650 | 2 | 4 | _aKnowledge Based Systems. |
650 | 2 | 4 | _aBusiness Information Systems. |
650 | 2 | 4 | _aComputer Application in Social and Behavioral Sciences. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789811973680 |
776 | 0 | 8 |
_iPrinted edition: _z9789811973703 |
830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-19-7369-7 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
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