Open AccessAllocation of Tasks in Crowdsourcing Problem using Parallel Tasking
Author(s) -
A. Punitha,
A.R. Visagan,
R Mahesh
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f8157.038620
Subject(s) - crowdsourcing , task (project management) , computer science , crowdsourcing software development , context (archaeology) , quality (philosophy) , human multitasking , human–computer interaction , plan (archaeology) , work (physics) , data science , software , world wide web , software development , engineering , cognitive psychology , psychology , mechanical engineering , paleontology , software construction , philosophy , history , systems engineering , epistemology , archaeology , biology , programming language
Crowdsourcing is a moderately new wonder in software engineering and programming designing. In crowdsourcing, a task is conveyed to a crowd of participants who will work on this task. Task allocation is then a significant aspect in the context of crowdsourcing. If done properly, it conveys victories dependent on the appropriate responses gave by the crowd. However, task allocation in crowdsourcing is certainly not an inconsequential issue. Factors like a task’s prerequisites, the knowledge required for its goals, and the size and heterogeneity of the participants in the crowd all impact task allocation, and subsequently, the expected quality of the task results. Right now, the execution of actions from a plan, that assists the dynamic task allocation in crowdsourcing systems, becomes relevant as an alternative solution. This paper formalizes task allocation in crowdsourcing scenarios as Allocation of Tasks in Crowdsourcing problem (ATCP). The fundamental objective of this paper is to allocate suitable tasks for appropriate workers with the dynamic profile creation of the user and the tasks.