{"product_id":"9783032294807","title":"Discount Quality for Responsible Data Science Human-in-the-Loop for Quality Data","description":"\u003ch3\u003eSpringerBriefs in Applied Sciences and Technology PoliMI SpringerBriefs\u003c\/h3\u003e\u003ch1\u003eDiscount Quality for Responsible Data Science\u003c\/h1\u003e\u003ch2\u003eHuman-in-the-Loop for Quality Data\u003c\/h2\u003e\u003ch3\u003eBarbara Pernici | Tiziana Catarci | Matteo Palmonari | Giovanni Simonini\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eComputers \/ Data Science \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\u003cp class=\"xmsonormal\" style=\"background: white;\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003eThis open access book presents a “discount”-quality approach to data preparation for scientific data analysis, a \u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm;\"\u003ecritical\u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003e \u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm;\"\u003eprerequisite in modern applications\u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003e \u003cspan lang=\"EN-US\"\u003esuch as\u003c\/span\u003e\u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm;\"\u003e data analysis projects, Artificial Intelligence, and Machine Learning\u003c\/span\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003e. It discusses advanced techniques for \u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm;\"\u003efostering\u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003e \u003cspan lang=\"EN-US\"\u003eresponsible data science, i.e., designing sustainable data analysis pipelines based on Human-In-The-Loop (HITL) approaches to achieve high-quality data. It investigates developing task- and context-driven sustainable approaches for data preparation, \u003c\/span\u003e\u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm;\"\u003edrawing\u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003e \u003cspan lang=\"EN-US\"\u003eon methods and theories to reduce annotations and processing space and time, and considering the estimation of the necessary human computing effort and the requirements of the specific task.\u003c\/span\u003e\u003c\/span\u003e\u003cspan lang=\"EN-US\" style=\"font-family: 'Aptos',sans-serif; color: black; mso-color-alt: windowtext; mso-ansi-language: EN-US;\"\u003e \u003c\/span\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003eThe contributions \u003c\/span\u003e\u003cspan style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm;\"\u003eaddress \u003c\/span\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003ekey aspects related to data ecosystems, data preparation pipelines, data quality evaluation and improvement, \u003c\/span\u003e\u003cspan lang=\"EN-GB\" style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-GB;\"\u003eon-demand approaches to data preparation, data enrichment, and human\u003c\/span\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'inherit',serif; color: black; mso-color-alt: windowtext; border: none windowtext 1.0pt; mso-border-alt: none windowtext 0cm; padding: 0cm; mso-ansi-language: EN-US;\"\u003e factors in data preparation.\u003c\/span\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e16 August 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003ePolitecnico di Milano\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9783032294807\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003ePaperback \/ softback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e94\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Politecnico di Milano","offers":[{"title":"Default Title","offer_id":49940120633484,"sku":"9783032294807","price":34.19,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783032294807.jpg?v=1781058141","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783032294807","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}