Incentive-aware Task Location in Spatial Crowdsourcing

Fei Zhu, Shushu Liu, Junhua Fang, An Liu*

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

Abstrakti

With the popularity of wireless network and mobile devices, spatial crowdsourcing has gained much attention from both academia and industry. One of the critical components in spatial crowdsourcing is task-worker matching, where workers are assigned to tasks to meet some pre-defined objectives. Previous works generally assume that the locations of tasks are known in advance. However, this does not always hold, since in many real world applications where to put tasks is not specific and needs to be determined on the fly. In this paper, we propose Incentive-aware Task Location (ITL), a novel problem in spatial crowdsourcing. Given a location-unspecific task with a fixed budget, the ITL problem seeks multiple locations to place the task and allocates the given budget to each location, such that the number of workers who are willing to participate the task is maximized. We prove that the ITL problem is NP-hard and propose three heuristic methods to solve it, including even clustering, uneven clustering and greedy location methods. Through extensive experiments on a real dataset, we demonstrate the efficiency and effectiveness of the proposed methods.

AlkuperäiskieliEnglanti
OtsikkoDatabase Systems for Advanced Applications
AlaotsikkoProceedings of 26th International Conference (DASFAA 2021), Part I
ToimittajatChristian S. Jensen, Ee-Peng Lim, De-Nian Yang, Wang-Chien Lee, Vincent S. Tseng, Vana Kalogeraki, Jen-Wei Huang, Chih-Ya Shen
KustantajaSpringer Science and Business Media Deutschland GmbH
Sivut650-657
Sivumäärä8
ISBN (elektroninen)9783030731946
ISBN (painettu)9783030731939
DOI - pysyväislinkit
TilaJulkaistu - huhtikuuta 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Database Systems for Advanced Applications - Virtual, Online, Taipei, Taiwan
Kesto: 11 huhtikuuta 202114 huhtikuuta 2021
Konferenssinumero: 26
http://dm.iis.sinica.edu.tw/DASFAA2021/

Julkaisusarja

NimiLecture Notes in Computer Science
KustantajaSpringer
Vuosikerta12681
ISSN (painettu)0302-9743
ISSN (elektroninen)1611-3349

Conference

ConferenceInternational Conference on Database Systems for Advanced Applications
LyhennettäDASFAA
MaaTaiwan
KaupunkiTaipei
Ajanjakso11/04/202114/04/2021
www-osoite

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