Tasks that require users to have expert knowledge are diffi- cult to crowdsource. They are mostly too complex to be carried out by non-experts and the available experts in the crowd are difficult to target. Adapting an expert task into a non-expert user task, thereby enabling the ordinary “crowd” to accomplish it, can be a useful approach. We studied whether a simplified version of an expert annotation task can be carried out by non-expert users. Users conducted a game-style annota- tion task of oil paintings. The obtained annotations were compared with those from experts. Our results show a significant agreement between the annotations done by experts and non-experts, that users improve over time and that the aggregation of users’ annotati...
Data collection by means of crowdsourcing can be costly or produce inaccurate results. Methods have ...
Crowdsourcing is a computational paradigm whose distinctive feature is the involvement of human work...
While human annotation is crucial for many natural language processing tasks, it is often very expen...
Tasks that require users to have expert knowledge are diffi- cult to crowdsource. They are mostly to...
Online collections provided by museums are increasingly opened for contributions from users outside ...
The results of our exploratory study provide new insights to crowdsourcing knowledge intensive tasks...
Large datasets such as Cultural Heritage collections require detailed annotations when digitised and...
The creation of golden standard datasets is a costly business. Optimally more than one judgment per ...
The creation of golden standard datasets is a costly business. Optimally more than one judgment per ...
Cultural heritage institutions more and more provide online access to their collections. Collections...
Experts or (crowd of) non-experts ? the question of the annotators’ expertise viewed from crowdsourc...
Crowdsourcing refers to distributing microtasks to an unknown group of online workers. Given that wo...
Labeled data is a prerequisite for successfully applying machine learning techniques to a wide range...
Crowdsourcing can efficiently complete tasks that are difficult to automate, but the quality of crow...
International audienceCrowdsourcing platforms enable to propose simple human intelligence tasks to a...
Data collection by means of crowdsourcing can be costly or produce inaccurate results. Methods have ...
Crowdsourcing is a computational paradigm whose distinctive feature is the involvement of human work...
While human annotation is crucial for many natural language processing tasks, it is often very expen...
Tasks that require users to have expert knowledge are diffi- cult to crowdsource. They are mostly to...
Online collections provided by museums are increasingly opened for contributions from users outside ...
The results of our exploratory study provide new insights to crowdsourcing knowledge intensive tasks...
Large datasets such as Cultural Heritage collections require detailed annotations when digitised and...
The creation of golden standard datasets is a costly business. Optimally more than one judgment per ...
The creation of golden standard datasets is a costly business. Optimally more than one judgment per ...
Cultural heritage institutions more and more provide online access to their collections. Collections...
Experts or (crowd of) non-experts ? the question of the annotators’ expertise viewed from crowdsourc...
Crowdsourcing refers to distributing microtasks to an unknown group of online workers. Given that wo...
Labeled data is a prerequisite for successfully applying machine learning techniques to a wide range...
Crowdsourcing can efficiently complete tasks that are difficult to automate, but the quality of crow...
International audienceCrowdsourcing platforms enable to propose simple human intelligence tasks to a...
Data collection by means of crowdsourcing can be costly or produce inaccurate results. Methods have ...
Crowdsourcing is a computational paradigm whose distinctive feature is the involvement of human work...
While human annotation is crucial for many natural language processing tasks, it is often very expen...