Recommender Systems for Software Project Managers
Abstract
The design of recommendation systems is based on complex information processing and big data interaction. This personalized view has evolved into a hot area in the past decade, where applications might have been proved to help for solving problem in the software development field. Therefore, with the evolvement of Recommendation System in Software Engineering (RSSE), the coordination of software projects with their stakeholders is improving. This experiment examines four open source recommender systems and implemented a customized recommender engine with two industrial-oriented packages: Lenskit and Mahout. Each of the main functions was examined and issues were identified during the experiment.
Cite
@article{arxiv.2108.04311,
title = {Recommender Systems for Software Project Managers},
author = {Liang Wei and Luiz Fernando Capretz},
journal= {arXiv preprint arXiv:2108.04311},
year = {2021}
}
Comments
Proceedings of the Evaluation and Assessment in Software Engineering (EASE 2021), 6 pages