---
license: cc-by-4.0
pretty_name: 'Flight Booking App Screen Recording Dataset'
language:
- en
tags:
- screen-recording
- flight-booking
- travel
- mobile-app
- user-interface
- clickstream
- usability
- ai-research
- video-to-text
- ui-analysis
task_categories:
- video-classification
- video-text-to-text
size_categories:
- 1K<n<10K
---

# Flight Booking App Screen Recording Dataset
*This dataset contains high-quality screen recordings of user interactions on flight booking applications. It has been carefully curated, cleaned, and anonymized to ensure accuracy, completeness, and compliance with privacy standards, making it suitable for AI training, UX research, and user behavior analysis.*

## Contact
For queries or collaborations related to this dataset, contact:  
  - anoushka@kgen.io  
  - abhishek.vadapalli@kgen.io  

## Supported Tasks

- **Task Categories**:  
  - Video Classification  
  - Video-to-Text Generation  

- **Supported Tasks**:  
  - Automatic captioning of flight booking workflows  
  - User journey segmentation (search → select → checkout → ticket confirmation)  
  - Action recognition (e.g., origin/destination selection, date picking, seat selection, payment)  
  - UX pattern analysis for flight booking apps  
  - Behavioral modeling for personalized travel recommendations  
  - Multimodal research in travel-tech applications  

## Languages

- **Primary Language**: English (UI, flight listings, and user interactions)  

## Dataset Creation

### Curation Rationale
This dataset was created to advance AI research in travel applications and flight booking workflows. It enables models to understand step-by-step booking journeys, user decision-making, and preferences for better UX design and intelligent recommendation systems.

### Source Data
- **Contributors**: Simulated user sessions on flight booking apps  
- **Collection Process**: Screen recordings of diverse user activities including searching flights, applying filters, selecting flights and seats, completing payment, and receiving confirmation. All personally identifiable information (PII) is anonymized or removed.  

### Other Known Limitations
- **Size**: Dataset may not cover all edge cases (e.g., cancellations, refunds, customer service interactions)  
- **Bias**: Recorded sessions may overrepresent certain routes, airlines, or traveler types  
- **Platform-Specificity**: May not generalize across all flight booking apps or regional platforms  

## Intended Uses

### ✅ Direct Use
- Training AI models for action recognition in flight booking workflows  
- Research in human-computer interaction (HCI) and usability testing  
- Automatic summarization of booking journeys  
- Academic research in travel-tech UX and behavioral AI  

### ❌ Out-of-Scope Use
- Tracking or surveillance of real users without explicit consent  
- Commercial exploitation without attribution or ethical clearance  
- Extraction of sensitive payment or personal information  
- Real-time monitoring or decision-making without human oversight  

## License

CC BY 4.0