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TU Berlin

Inhalt des Dokuments

Next Generation Crowdsourcing

Overview of Activities:

Platform:

  • Fundamental aspects of Crowdsourcing Platforms
  • Workflow Design
  • Combination of Human Computation and AI

Workers:

  • Motivation of Workers
  • Gamification in Volunteer Crowdsourcing
  • Personalized/adaptive design to Increase Performance
  • Quality Control Mechanisms (Data Reliability, Agreement)

Application of Crowdsourcing:

  • Speech Quality Assessment using Crowdsourcing approach (ITU-T Standardization)
  • Text Simplification and Text Complexity: einfaches-wiki.de
  • Translation
  • Internal Crowdsourcing
  • Gaming QoE Assessment using Crowdsourcing approcach

 

Our research extends to the following areas:

Building on Crowdsourcing

- Mobile crowdsourcing (in the field)

- Crowd assessments: Usability, UX, QoE

- Privacy and confidentiality in crowdsourcing

- Mobile street application, urban mobility, city guarding

- Data collection in the field: crowd as (continuous) sensors

- Data management (clean, index, verify, tag, label, translate, etc. )

 

Improving Crowdsourcing

- Real-time interaction, human computation as a service, (HuaaS)

- Privacy and security in crowdsourcing

- Motivation in crowdsourcing, gamification

- Quality control (pattern recognition, cheater detection, anomaly)

- Automatic user segmentation (clustering)

- Training, E-learning and building expert-crowds

- Task complexity modeling

- Crowd and user biasses, subjective normaliztion

- Scalable Crowdsourcing, Robustness, Realiability in Engineering

- Quality in Crowdsourcing (quality of opinion, audio/video, reliability) 

 

Crowdee Start-Up 

Start-Up from TU Berlin and Telekom Innovation Laboratories

Start-UP: Crowdee (external webpage)
Research Project: Crowdee (internal website)

 

Core Team

 

Running Projects

 

Past Projects

Zusatzinformationen / Extras

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