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Tagasi otsingutulemusse

Pealkiri	Transparent data mining for big and small data / Tania Cerquitelli, Daniele Quercia, Frank Pasquale, editors
Ilmunud	Cham : Springer, 2017
Kirjeldus	xv, 215 lk. : ill. ; 25 cm

Püsilink	https://www.ester.ee/record=b4674403~S1*est

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ASUKOHT	KOHAVIIT	STAATUS	MÄRKUSED
RaRa 1.korrus Narva mnt	658/TRA Digitaalmajandus	KOHAL

Tagasi kataloogi

Pealkiri	Transparent data mining for big and small data / Tania Cerquitelli, Daniele Quercia, Frank Pasquale, editors
Ilmunud	Cham : Springer, 2017
Kirjeldus	xv, 215 lk. : ill. ; 25 cm

ISBN	9783319540238 (köites)
Sarjaandmed	Studies in big data, 219-6503 ; 11
Märkused	Bibliograafia artiklite lõpus
Sisukord	Preface; Contents; List of Contributors; Acronyms; Part I Transparent Mining; The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good; 1 Introduction; 2 The Rise of Data-Driven Decision-Making for Social Good; 2.1 Criminal Behavior Dynamics and Predictive Policing; 2.2 Socio-Economic Deprivation and Financial Inclusion; 2.3 Public Health; 3 The Dark Side of Data-Driven Decision-Making for Social Good; 3.1 Computational Violations of Privacy; 3.2 Information Asymmetry and Lack of Transparency; 3.3 Social Exclusion and Discrimination 4 Requirements for Positive Disruption of Data-Driven Policies4.1 User-Centric Data Ownership and Management; 4.2 Algorithmic Transparency and Accountability; 4.3 Living Labs to Experiment with Data-Driven Policies; 5 Conclusion; References; Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens; Abbreviations; 1 Introduction; 2 Transparency Model; 3 Case Studies; 3.1 Editorial Transparency in an Automated Newsbot; 3.2 Critical Application of the Algorithmic Transparency Model; 3.2.1 Google's Issue Guide; 3.2.2 BuzzFeed News Investigation; 4 Discussion 5.1 The Web Browser as a Privacy Regulator5.2 Open Standards and Privacy; 5.3 The Market for Lemons and First-Party Accountability; 5.4 Design for Measurement; 6 The Future of Transparency Research; 7 Conclusion; References; Part II Algorithmic Solutions; Algorithmic Transparency via Quantitative Input Influence; Abbreviation; Symbols; 1 Introduction; 2 Unary QII; 3 Transparency Schema; 4 Set and Marginal QII; 4.1 Cooperative Games and Causality; 4.2 Axiomatic Treatment of the Shapley Value; 5 Experimental Evaluation; 5.1 Unary QII Measures; 5.2 Personalized Transparency Reports 6 QII for Fairness7 Related Work; 8 Conclusion & Future Work; References; Learning Interpretable Classification Rules with Boolean Compressed Sensing; Abbreviations; 1 Introduction; 2 Boolean Rule Learning as Group Testing; 2.1 The Group Testing Problem; 2.2 Supervised Classification Rule Formulation; 3 LP Relaxation; 3.1 Boolean Compressed Sensing-Based Formulation; 3.2 Recovery Guarantees; 3.3 Multi-Category Classification; 4 Learning Scorecards Using Threshold Group Testing; 4.1 Threshold Group Testing; 4.2 LP Formulation for Threshold Group Testing
Märksõnad	suurandmed
	algoritmid
	andmebaasid
	andmekaeve
	intellektuaalne omand
	rahvusvaheline õigus
	õiguslikud aspektid
	arvutiteadus
	artiklikogumikud (vormimärksõna)
Täiendkirjed	Cerquitelli, Tania, toimetaja
	Quercia, Daniele, toimetaja
	Pasquale, Frank, toimetaja
UDK	004 (082)

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