MCDM Approach for Assigning Task to the Workers by Selected Features Based on Multiple Criteria in Crowdsourcing

Abstract

Crowdsourcing in simple words is the outsourcing of a task to an online market to be performed by a diverse group of crowds in order to utilize human intelligence. Due to online labor markets and performing parallel tasks, the crowdsourcing activity is time- and cost-efficient. During crowdsourcing activity, selecting the proper labeled tasks and assigning them to an appropriate worker are a challenge for everyone. A mechanism has been proposed in the current study for assigning the task to the workers. The proposed mechanism is a multicriteria-based task assignment (MBTA) mechanism for assigning the task to the most suitable worker. This mechanism uses approaches for weighting the criteria and ranking the workers. These MCDM methods are Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Criteria have been made for the workers based on the identified features in the literature. Weight has been assigned to these selected features/criteria with the help of the CRITIC method. The TOPSIS method has been used for the evaluation of workers, with the help of which the ranking of workers is performed in order to get the most suitable worker for the selected tasks to be performed. The proposed work is novel in several ways; for example, the existing methods are mostly based on single criterion or some specific criteria, while this work is based on multiple criteria including all the important features. Furthermore, it is also identified from the literature that none of the authors used MCDM methods for task assignment in crowdsourcing before this research.

RETRACTED ARTICLE: Decision support system for effective action recognition of track and field sports using ant colony optimization

“…The relevant features are then fed into the proposed system to enhance the learning process of machine and to provide accurate results. [32,33], device selection [34], shape optimization, and gene identi cation [35] are some examples of practical optimization challenges. ACO is a feasible approach for improving prediction.…”

Secured MCDM Model for Crowdsource Business Intelligence

“…Everyone finds it difficult to choose the right jobs with the relevant labels and give them to the right workers during a crowdsourcing exercise. In this study [19], the authors have suggested a mechanism for allocating the task to the workers. To give the task to the most qualified worker, a multicriteria-based task assignment (MBTA) mechanism is developed.…”