Crowd-Machine Collaboration for Item Screening

Bibliographic Details
Parent link:	World Wide Web Conference (WWW 2018).— 2018.— [P. 95-96]
Corporate Author:	Национальный исследовательский Томский политехнический университет Школа инженерного предпринимательства
Other Authors:	Krivosheev E. Evgeny, Harandizadeh B. Bahareh, Benatallah B. Boualem, Casati F. Fabio
Summary:	Title screen In this paper we describe how crowd and machine classifier can beefficiently combined to screen items that satisfy a set of predicates.We show that this is a recurring problem in many domains, presentmachine-human (hybrid) algorithms that screen items efficientlyand estimate the gain over human-only or machine-only screeningin terms of performance and cost.
Language:	English
Published:	2018
Subjects:	труды учёных ТПУ электронный ресурс crowdsourcing machine learning hybrid systems classification краудсорсинг машинное обучение гибридные системы классификация
Online Access:	https://doi.org/10.1145/3184558.3186946
Format:	Electronic Book Chapter
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=659537

Description
Summary:	Title screen In this paper we describe how crowd and machine classifier can beefficiently combined to screen items that satisfy a set of predicates.We show that this is a recurring problem in many domains, presentmachine-human (hybrid) algorithms that screen items efficientlyand estimate the gain over human-only or machine-only screeningin terms of performance and cost.
DOI:	10.1145/3184558.3186946

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