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Authors: Beatrice Valeri 1 ; Shady Elbassuoni 2 and Sihem Amer-Yahia 3

Affiliations: 1 University of Trento, Italy ; 2 American University of Beirut, Lebanon ; 3 University of Grenoble, France

Keyword(s): Crowdsourcing, Task Assignment, Cheater Identification.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Collective Intelligence ; Enterprise Information Systems ; Recommendation Systems ; Software Agents and Internet Computing

Abstract: We address the problem of acquiring reliable ratings of items such as restaurants or movies from the crowd. A reliable rating is a truthful rating from a worker that is knowledgeable enough about the item she is rating. We propose a crowdsourcing platform that considers workers’ expertise with respect to the items being rated and assigns workers the best items to rate. In addition, our platform focuses on acquiring ratings for items that only have a few ratings. Traditional crowdsourcing platforms are not suitable for such a task for two reasons. First, ratings are subjective and there is no single correct rating for an item which makes most existing work on predicting the expertise of crowdsourcing workers inapplicable. Second, in traditional crowdsourcing platforms there is no control over task assignment by the requester. In our case, we are interested in providing workers with the best items to rate based on their estimated expertise for the items and the number of ratings the it ems have. We evaluate the effectiveness of our system using both synthetic and real-world data about restaurants. (More)

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Paper citation in several formats:
Valeri, B.; Elbassuoni, S. and Amer-Yahia, S. (2016). Crowdsourcing Reliable Ratings for Underexposed Items. In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST; ISBN 978-989-758-186-1; ISSN 2184-3252, SciTePress, pages 75-86. DOI: 10.5220/0005770700750086

@conference{webist16,
author={Beatrice Valeri. and Shady Elbassuoni. and Sihem Amer{-}Yahia.},
title={Crowdsourcing Reliable Ratings for Underexposed Items},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST},
year={2016},
pages={75-86},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005770700750086},
isbn={978-989-758-186-1},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST
TI - Crowdsourcing Reliable Ratings for Underexposed Items
SN - 978-989-758-186-1
IS - 2184-3252
AU - Valeri, B.
AU - Elbassuoni, S.
AU - Amer-Yahia, S.
PY - 2016
SP - 75
EP - 86
DO - 10.5220/0005770700750086
PB - SciTePress