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TU Berlin

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Crowdsourcing and Open Data

Core Team

 

Topics

Platform

  • Fundamental Aspects of Crowdsourcing Platforms
  • High Quality Crowd-Workflow Design
  • Combination of Human Computation and AI
  • Open Data, and Open Science (open-science.berlin)

Workers

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

Application of Crowdsourcing

  • Crowd- and AI-based Hybrid Workflows (error correction and performance boost by adding crowd-services to support AI) 
  • Crowd- and AI-based Translation Workflows
  • Crowd- and AI-based Text Summarization Workflows
  • Crowd- and AI-based Knowledge Graph and Chatbot Supporting Workflows
  • Crowd- and AI-based Chatbot/ Dialog Flow Supervision and in-time Correction
  • Crowd- and AI-based Information Learning (autonomous knowledge base updates)
  • Internal Crowdsourcing (employee sourcing)
  • Gaming QoE Assessment using Crowdsourcing
  • Speech Quality Assessment using Crowdsourcing approach (ITU-T Standardization)
  • Text Simplification and Text Complexity: einfaches-wiki.de

 

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 biases, subjective normalization
- Scalable Crowdsourcing, Robustness, Reliability in Engineering
- Quality in Crowdsourcing (quality of opinion, audio/video, reliability) 

 

Start-Up

  • CrowdeeHigh Quality Large Scale Crowdsourcing for Studies and AI-related Data Acquisition: (Start-Up from QU TU Berlin)

 

Running Projects

 

Past Projects

 

Zusatzinformationen / Extras

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