Logo image
Investigating Aspects of Platform Growth on Crowdsource Driven Recommendation Services
Conference proceeding

Investigating Aspects of Platform Growth on Crowdsource Driven Recommendation Services

Julian Jarrett, M. Brian Blake and IEEE
2018 4TH IEEE INTERNATIONAL CONFERENCE ON COLLABORATION AND INTERNET COMPUTING (CIC 2018)
01 Jan 2018

Abstract

Computer Science Computer Science, Theory & Methods Engineering Engineering, Electrical & Electronic Science & Technology Technology
With the advent of the Internet, crowdsourcing platforms are a viable option for the solicitation of labor and distribution of tasks, online. As platforms develop, expand, and evolve, they employ various approaches to assist job owners and workers in searching for suitable tasks where workers' skillsets and job requirements are aligned and compatible. Recommender systems provide a suitable candidate for such purposes and can assist in worker-job matching. In this paper, through experimentation, we investigate the effect that growth in the labor force and job catalog has on the times to produce recommendations, the jobs recommended to workers and the precision of our collaborative-filtering-oriented bottom-up recommender.

Metrics

10 Record Views

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#11 Sustainable Cities and Communities
#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Web of Science research areas
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Logo image