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GP-selector: a generic participant selection framework for mobile crowdsourcing systems

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GP-selector : a generic participant selection framework for mobile crowdsourcing systems. / Wang, Jiangtao; Wang, Yasha; Wang, Leye; He, Yuanduo.

In: World Wide Web , Vol. 21, No. 3, 01.05.2018, p. 759-782.

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Wang, Jiangtao ; Wang, Yasha ; Wang, Leye ; He, Yuanduo. / GP-selector : a generic participant selection framework for mobile crowdsourcing systems. In: World Wide Web . 2018 ; Vol. 21, No. 3. pp. 759-782.

Bibtex

@article{34414feff4dd447bb866962babd62edd,
title = "GP-selector: a generic participant selection framework for mobile crowdsourcing systems",
abstract = "Participant selection is a common and crucial function for mobile crowdsourcing (MCS) systems or platforms. This paper introduces a generic framework, named GP-Selector, to handle the participant selection from MCS task creation time to runtime. Compared to existing approaches, ours has the following two unique features. 1) In the task creation time, it assists task creators with diverse levels of programming skills to define basic requirements of participant selection. 2) In the runtime, it adopts a two-phase selection process to select participants who not only meet the basic requirements but also are willing to accept the task. Specifically, we utilize the state-of-the-art techniques including ontology modeling, end-user programming and multi-classifier fusion to implement GP-Selector. We evaluate GP-Selector extensively in three aspects: the end-user task creation, the expressiveness of the core ontology model, and the willingness-based selection algorithm. The evaluation results demonstrate the usability and effectiveness.",
keywords = "Mobile crowdsourcing, Mobile crowdsensing, Participant selection",
author = "Jiangtao Wang and Yasha Wang and Leye Wang and Yuanduo He",
year = "2018",
month = may,
day = "1",
doi = "10.1007/s11280-017-0480-y",
language = "English",
volume = "21",
pages = "759--782",
journal = "World Wide Web ",
issn = "1386-145X",
publisher = "Springer New York",
number = "3",

}

RIS

TY - JOUR

T1 - GP-selector

T2 - a generic participant selection framework for mobile crowdsourcing systems

AU - Wang, Jiangtao

AU - Wang, Yasha

AU - Wang, Leye

AU - He, Yuanduo

PY - 2018/5/1

Y1 - 2018/5/1

N2 - Participant selection is a common and crucial function for mobile crowdsourcing (MCS) systems or platforms. This paper introduces a generic framework, named GP-Selector, to handle the participant selection from MCS task creation time to runtime. Compared to existing approaches, ours has the following two unique features. 1) In the task creation time, it assists task creators with diverse levels of programming skills to define basic requirements of participant selection. 2) In the runtime, it adopts a two-phase selection process to select participants who not only meet the basic requirements but also are willing to accept the task. Specifically, we utilize the state-of-the-art techniques including ontology modeling, end-user programming and multi-classifier fusion to implement GP-Selector. We evaluate GP-Selector extensively in three aspects: the end-user task creation, the expressiveness of the core ontology model, and the willingness-based selection algorithm. The evaluation results demonstrate the usability and effectiveness.

AB - Participant selection is a common and crucial function for mobile crowdsourcing (MCS) systems or platforms. This paper introduces a generic framework, named GP-Selector, to handle the participant selection from MCS task creation time to runtime. Compared to existing approaches, ours has the following two unique features. 1) In the task creation time, it assists task creators with diverse levels of programming skills to define basic requirements of participant selection. 2) In the runtime, it adopts a two-phase selection process to select participants who not only meet the basic requirements but also are willing to accept the task. Specifically, we utilize the state-of-the-art techniques including ontology modeling, end-user programming and multi-classifier fusion to implement GP-Selector. We evaluate GP-Selector extensively in three aspects: the end-user task creation, the expressiveness of the core ontology model, and the willingness-based selection algorithm. The evaluation results demonstrate the usability and effectiveness.

KW - Mobile crowdsourcing

KW - Mobile crowdsensing

KW - Participant selection

U2 - 10.1007/s11280-017-0480-y

DO - 10.1007/s11280-017-0480-y

M3 - Journal article

VL - 21

SP - 759

EP - 782

JO - World Wide Web

JF - World Wide Web

SN - 1386-145X

IS - 3

ER -