Litcius/Paper detail

Structured dataset of human-machine interactions enabling adaptive user interfaces

Angela Carrera-Rivera, Daniel Reguera-Bakhache, Félix Larrinaga, Ganix Lasa, Iñaki Garitano

2023Scientific Data11 citationsDOIOpen Access PDF

Abstract

This article introduces a dataset of human-machine interactions collected in a controlled and structured manner. The aim of this dataset is to provide insights into user behavior and support the development of adaptive Human-Machine Interfaces (HMIs). The dataset was generated using a custom-built application that leverages formally defined User Interfaces (UIs). The resulting interactions underwent processing and analysis to create a suitable dataset for professionals and data analysts interested in user interface adaptations. The data processing stage involved cleaning the data, ensuring its consistency and completeness. A data profiling analysis was conducted for checking the consistency of elements in the interaction sequences. Furthermore, for the benefit of researchers, the code used for data collection, data profiling, and usage notes on creating adaptive user interfaces are made available. These resources offer valuable support to those interested in exploring and utilizing the dataset for their research and development efforts in the field of human-machine interfaces.

Topics & Concepts

Profiling (computer programming)Computer scienceConsistency (knowledge bases)User interfaceHuman–computer interactionData scienceData miningArtificial intelligenceProgramming languageContext-Aware Activity Recognition SystemsData Visualization and AnalyticsTime Series Analysis and Forecasting