On the Impact of Predicate Complexity in Crowdsourced Classification Tasks; Web Search and Data Mining, WSDM 2021

Dades bibliogràfiques
Parent link:Web Search and Data Mining, WSDM 2021.— 2021.— [P. 67-75]
Autor corporatiu: Национальный исследовательский Томский политехнический университет Институт социально-гуманитарных технологий Кафедра экономики Международная научно-образовательная лаборатория технологий улучшения благополучия пожилых людей, Национальный исследовательский Томский политехнический университет Школа базовой инженерной подготовки Отделение социально-гуманитарных наук
Altres autors: Ramirez J. Jorge, Baez M. Marcos, Casati F. Fabio, Cernuzzi L. Luca, Benatallah B. Boualem, Taran Е. А. Ekaterina Aleksandrovna, Malanina V. A. Veronika Anatolievna
Sumari:Title screen
This paper explores and offers guidance on a specific and relevant problem in task design for crowdsourcing: how to formulate a complex question used to classify a set of items. In micro-task markets, classification is still among the most popular tasks. We situate our work in the context of information retrieval and multi-predicate classification, i.e., classifying a set of items based on a set of conditions. Our experiments cover a wide range of tasks and domains, and also consider crowd workers alone and in tandem with machine learning classifiers. We provide empirical evidence into how the resulting classification performance is affected by different predicate formulation strategies, emphasizing the importance of predicate formulation as a task design dimension in crowdsourcing.
Idioma:anglès
Publicat: 2021
Matèries:
Accés en línia:https://doi.org/10.1145/3437963.3441831
Format: Electrònic Capítol de llibre
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=665083