Understand system's relative effectiveness using adapted confusion matrix

Authors: Jiang, N. and Liu, H.

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 8012 LNCS

Issue: PART 1

Pages: 294-302

eISSN: 1611-3349

ISSN: 0302-9743

DOI: 10.1007/978-3-642-39229-0_32


The effectiveness of a system refers to the accuracy and completeness with which users achieve specified goals. These two aspects are interpreted as errors and completion in the context of usability testing. However, a holistic view of effectiveness is not straight forward to establish in a comparative test because the two measures focus on different aspects of user outputs. In this paper, we propose a predictive method to measure a system's relative effectiveness based on its own performance prediction. We achieve it by using an adapted confusion matrix to establish a correlation model between the two measures. A real-world use case is provided to demonstrate the usefulness of our method in a comparative study of the two websites. © 2013 Springer-Verlag Berlin Heidelberg.

Source: Scopus

Preferred by: Nan Jiang

Understand System’s Relative Effectiveness Using Adapted Confusion Matrix

Authors: Jiang, N. and Liu, H.

Conference: HCI International 2013

Dates: 21-26 July 2013

Source: Manual