In this paper, we present an initial implementation with experimental results of online profile learning in Argo+, a framework for crowdsourcing task routing characterized by i) feature-based representation of both tasks and workers, and ii) learning techniques inspired to Rocchio relevance feedback for prediction of the most appropriate task to execute by a given worker.
Introducing Online Profile Learning in Crowdsourcing Task Routing / S. Castano, A. Ferrara, S. Montanelli (CEUR WORKSHOP PROCEEDINGS). - In: SEBD 2018 : Italian Symposium on Advanced Database Systems / [a cura di] S. Bergamaschi, T. Di Noia, A. Maurino. - [s.l] : CEUR-WS, 2018. - pp. 1-8 (( Intervento presentato al 26. convegno Italian Symposium on Advanced Database Systems, SEBD 2018 tenutosi a Castellaneta Marina nel 2018.
Introducing Online Profile Learning in Crowdsourcing Task Routing
S. Castano;A. Ferrara;S. Montanelli
2018
Abstract
In this paper, we present an initial implementation with experimental results of online profile learning in Argo+, a framework for crowdsourcing task routing characterized by i) feature-based representation of both tasks and workers, and ii) learning techniques inspired to Rocchio relevance feedback for prediction of the most appropriate task to execute by a given worker.File | Dimensione | Formato | |
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