Difference between revisions of "CrowdTruth: Crowdsourcing for Text, Video, Image or Sound Annotations"

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The CrowdTruth Framework implements an approach to machine-human computing for collecting annotation data on text, images, videos or sounds. The approach is focussed on collecting gold standard data for training and evaluation of cognitive computing systems.  
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The [http://crowdtruth.org/ CrowdTruth Framework] implements an approach to machine-human computing for collecting annotation data on text, images, videos or sounds. The approach is focussed on collecting gold standard data for training and evaluation of cognitive computing systems.  
  
The original framework was inspired by the IBM Watson project for providing improved (multi-perspective) gold standard (medical) text annotation data for the training and evaluation of various IBM Watson components, such as Medical Relation Extraction, Medical Factor Extraction and Question-Answer passage alignment.
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The original framework was inspired by the [http://www.research.ibm.com/labs/watson/ IBM Watson project] for providing improved (multi-perspective) gold standard (medical) text annotation data for the training and evaluation of various IBM Watson components, such as Medical Relation Extraction, Medical Factor Extraction and Question-Answer passage alignment.
  
 
There are number of Master Projects that can be done within this context:
 
There are number of Master Projects that can be done within this context:
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All those topics are done in collaboration with IBM Research & IBM NL, and for a selected top performing students internships at IBM can be provided.
 
All those topics are done in collaboration with IBM Research & IBM NL, and for a selected top performing students internships at IBM can be provided.
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Have a look at some of the [http://crowdtruth.org/presentations/ presentations] & [http://crowdtruth.org/papers/ papers] for inspirations about topics. Please make an appointment with [mailto:lora.aroyo@vu.nl Lora Aroyo] to discuss topics you are interested in.

Revision as of 07:13, 9 December 2014


About CrowdTruth: Crowdsourcing for Text, Video, Image or Sound Annotations

Description

The CrowdTruth Framework implements an approach to machine-human computing for collecting annotation data on text, images, videos or sounds. The approach is focussed on collecting gold standard data for training and evaluation of cognitive computing systems.

The original framework was inspired by the IBM Watson project for providing improved (multi-perspective) gold standard (medical) text annotation data for the training and evaluation of various IBM Watson components, such as Medical Relation Extraction, Medical Factor Extraction and Question-Answer passage alignment.

There are number of Master Projects that can be done within this context: - Natural-Language Processing focus - AI / Machine Learning focus - User Interfaces focus - Gamification focus - Crowdsourcing focus - Workflow optimization focus

All those topics are done in collaboration with IBM Research & IBM NL, and for a selected top performing students internships at IBM can be provided.

Have a look at some of the presentations & papers for inspirations about topics. Please make an appointment with Lora Aroyo to discuss topics you are interested in.