Authors:
Lucas Viana
1
;
Edson Oliveira
2
and
Tayana Conte
1
Affiliations:
1
Department of Computing, Universidade Federal do Amazonas (UFAM), Amazonas, Brazil
;
2
Secretaria de Estado da Fazenda (SEFAZ), Amazonas, Brazil
Keyword(s):
Interactive Labeling, Interactive Machine Learning, Interface Design, Interface Design for Interactive Machine Learning, Training Data.
Abstract:
Machine Learning (ML) systems have been widely used in recent years in different areas of human knowledge. However, to achieve highly accurate ML systems, it is necessary to train the ML model with data carefully labeled by specialists in the problem domain. In the context of ML and Human Computer Interaction (HCI), there are studies that propose interfaces that facilitate interactive labeling by domain specialists, in order to minimize effort and maximize productivity. This paper extends a previous secondary study that discusses some labeling systems. This paper proposes a catalog of design elements for the interface development of this type of system. We built the catalog based on the interface elements found in the studies analyzed in the previous secondary study. With this contribution, we expect to improve the development of better interfaces for interactive labeling systems and, thus, enhance the development of more accurate ML systems.