Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/4029
Title: Artest: the First Test Collection for Arabic Web Search With Relevance Rationales
Authors: Hasanain, M.
Barkallah, Y.
Suwaileh, R.
Kutlu, Mücahid
Elsayed, T.
Keywords: ad-hoc search
evaluation
less-resourced language
retrieval
Publisher: Association for Computing Machinery, Inc
Source: Hasanain, M., Barkallah, Y., Suwaileh, R., Kutlu, M., and Elsayed, T. (2020, July). Artest: The first test collection for arabic web search with relevance rationales. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2017-2020).
Abstract: The scarcity of Arabic test collections has long hindered information retrieval (IR) research over the Arabic Web. In this work, we present ArTest, the first large-scale test collection designed for the evaluation of ad-hoc search over the Arabic Web. ArTest uses ArabicWeb16, a collection of around 150M Arabic Web pages as the document collection, and includes 50 topics, 10,529 relevance judgments, and (more importantly) a rationale behind each judgment. To our knowledge, this is also the first IR test collection that includes rationales of primary assessors (i.e., topic developers) for their relevance judgments, exhibiting a useful resource for understanding the relevance phenomena. Finally, ArTest is made publicly-available for the research community. © 2020 ACM.
URI: https://hdl.handle.net/20.500.11851/4029
https://dl.acm.org/doi/10.1145/3397271.3401223
ISBN: 978-145038016-4
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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