Recommender Systems for Software Project Managers

被引：1

作者：

Wei, Liang ^{[1
]}

Capretz, Luiz Fernando ^{[2
]}

机构：

[1] Precima Inc, Toronto, ON, Canada

[2] Western Univ, Dept Elect & Comp Engn, London, ON, Canada

来源：

PROCEEDINGS OF EVALUATION AND ASSESSMENT IN SOFTWARE ENGINEERING (EASE 2021) | 2021年

关键词：

Recommender Engine; Recommendation System; Recommendation System in Software Engineering; RSSE; Project Management;

D O I：

10.1145/3463274.3463951

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

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.

引用

页码：412 / 417

页数：6

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