Leal, Fátima, Veloso, Bruno, Malheiro, Benedita, González-Vélez, Horacio and Burguillo, Juan Carlos (2020) A 2020 perspective on “Scalable modelling and recommendation using wiki-based crowdsourced repositories:” Fairness, scalability, and real-time recommendation. Electronic Commerce Research and Applications, 40. p. 100951. ISSN 1567-4223
Full text not available from this repository.Abstract
Wiki-based crowdsourced data sources generally lack reliability, as their provenance is not intrinsically marshalled. By using recommendation, one may arguably assess the reliability of wiki-based repositories in order to identify the most interesting articles for a given domain. In this commentary, we explore current trends in scalable modelling and recommendation methods based on side information such as the quality and popularity of wiki articles. The systematic parallelization of such profiling and recommendation algorithms allows the concurrent processing of distributed crowdsourced Wikidata repositories. These algorithms, which perform incremental updating, need further research to improve the performance and generate up-to-date high-quality recommendations. This article builds upon our previous work (Leal et al., 2019) by extending the literature review and identifying important trends and challenges pertaining to crowdsourcing platforms, particularly those of Wikidata provenance.
Item Type: | Article |
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Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software T Technology > T Technology (General) > Information Technology > Cloud computing |
Divisions: | School of Computing > Staff Research and Publications |
Depositing User: | Caoimhe Ní Mhaicín |
Date Deposited: | 28 Feb 2020 12:07 |
Last Modified: | 28 Feb 2020 12:09 |
URI: | https://norma.ncirl.ie/id/eprint/4131 |
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