Towards Clasification Exploration in Spatial Crowdsourcing Domain: A Systematic Literature Review
Main Article Content
Abstract
Today, spatial crowdsourcing concept has been widely applied in various fields. The increasing ofmobile user and adoption of social network has catalyst spatial crowdsourcing growth. It has madevarious types of data to be easily collected and transmitted from different geographical location.However, the massive amounts of task in spatial area bring challenges for the online system tomanage especially when the task is heterogeneous, and the interactions are dynamic. Such scenario
has alerted the researchers to understand different types of information in order to make taskassignment reliable and efficient.This study investigates current state of task assignment for spatialcrowdsourcing. It basically, aims to identify several issues like trend in publication and crowdcomputing areas that studies task assignment in crowdsourcing. We used Systematic LiteratureReview (SLR) method for analysing the trends and significance of task classification for betterdynamic crowd-computing.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.