Title :
Automated assessment of correctness of recommendation systems
Author :
Lozano, Angela ; Kellens, Andy ; Mens, Kim
Author_Institution :
Univ. Catholique de Louvain, Louvvain-La-Neuve, Belgium
Abstract :
Using a concrete example, this position paper makes a case for evaluating the correctness of software recommendation systems in an automated way, prior to conducting user studies, in order to assess the validity of the results and ideal configuration of the system to be evaluated.
Keywords :
recommender systems; automated assessment; software recommendation systems correctness; system configuration; user studies; Concrete; Context; Genetics; Gold; Maintenance engineering; Standards; Usability;
Conference_Titel :
Recommendation Systems for Software Engineering (RSSE), 2012 Third International Workshop on
Conference_Location :
Zurich
Print_ISBN :
978-1-4673-1758-0
DOI :
10.1109/RSSE.2012.6233410
