Crowd-Machine Collaboration for Item Screening

Evgeny Krivosheev, Bahareh Harandizadeh, Fabio Casati, Boualem Benatallah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we describe how crowd and machine classifier can be efficiently combined to screen items that satisfy a set of predicates. We show that this is a recurring problem in many domains, present machine-human (hybrid) algorithms that screen items efficiently and estimate the gain over human-only or machine-only screening in terms of performance and cost.

Original languageEnglish
Title of host publicationThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
PublisherAssociation for Computing Machinery, Inc
Pages95-96
Number of pages2
ISBN (Electronic)9781450356404
DOIs
Publication statusPublished - 23 Apr 2018
Externally publishedYes
Event27th International World Wide Web, WWW 2018 - Lyon, France
Duration: 23 Apr 201827 Apr 2018

Publication series

NameThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018

Conference

Conference27th International World Wide Web, WWW 2018
CountryFrance
CityLyon
Period23.4.1827.4.18

Keywords

  • crowdsourcing
  • human computation
  • hybrid classification
  • machine learning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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  • Cite this

    Krivosheev, E., Harandizadeh, B., Casati, F., & Benatallah, B. (2018). Crowd-Machine Collaboration for Item Screening. In The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018 (pp. 95-96). (The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018). Association for Computing Machinery, Inc. https://doi.org/10.1145/3184558.3186946