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Structured dataset of human-machine interactions enabling adaptive user interfaces
Angela Carrera-Rivera1, Daniel Reguera-Bakhache2, Felix Larrinaga2
1Faculty of Engineering, Electronics, and Computing. Mondragon Unibertsitatea, Arrasate-Mondragon, 20500, Spain. aicarrera@mondragon.edu.
Scientific Data
|November 25, 2023
Summary
A new dataset captures human-machine interactions to aid adaptive Human-Machine Interface (HMI) development. This structured data offers insights into user behavior for interface design and analysis.
Area of Science:
- Computer Science
- Human-Computer Interaction
- Data Science
Background:
- Human-Machine Interfaces (HMIs) are crucial for user interaction.
- Developing adaptive HMIs requires comprehensive user behavior data.
- Existing datasets may lack the structured detail needed for advanced HMI development.
Purpose of the Study:
- Introduce a novel dataset of human-machine interactions.
- Facilitate the development of adaptive Human-Machine Interfaces (HMIs).
- Provide insights into user behavior for UI adaptation.
Main Methods:
- Collected interaction data using a custom application with formally defined User Interfaces (UIs).
- Processed and analyzed interaction data, including cleaning and ensuring consistency.
- Conducted data profiling to verify interaction sequence consistency.
Main Results:
- Generated a structured dataset of human-machine interactions.
- The dataset is suitable for professionals and data analysts focused on UI adaptations.
- Associated code for data collection and profiling is publicly available.
Conclusions:
- The dataset provides a valuable resource for HMI research and development.
- Availability of data and code supports advancements in adaptive user interfaces.
- Enables deeper understanding and utilization of user interaction patterns.
