Cited By
View all- Dhinakaran KNedunchelian RBalasundaram A(2021)Crowdsourcing: Descriptive Study on Algorithms and Frameworks for PredictionArchives of Computational Methods in Engineering10.1007/s11831-021-09577-8Online publication date: 4-Apr-2021
Leveraging Crowdsourcing for the Thematic Annotation of the Qur'an
Pages 13 - 14
Abstract
In this paper, we illustrate how we leverage crowdsourcing to create workflows for knowledge engineering in specialized and knowledge intensive domains. We undertake the special case of the Arabic script of the Qur'an, a widely studied manuscript, and attempt to employ crowdsourcing methods for its thematic annotation at the sub-verse level, for which, there is no standardized knowledge model available to date. We demonstrate that our proposed method presents feasibility to achieve reliable annotations in an efficient and scalable manner. The proposed methodology and framework is meant to be generalizable to other knowledge intensive and specialized domains.
References
[1]
A. Basharat, I. B. Arpinar, S. Dastgheib, U. Kursuncu, K. Kochut, and E. Dogdu. Semantically enriched task and workflow automation in crowdsourcing for linked data management. International Journal of Semantic Computing, 8(04):415--439, 2014.
[2]
M. A. Sherif and A.-C. N. Ngomo. Semantic Quran - a multilingual resource for natural-language processing. Semantic Web, 6(4):339--345, 2015.
Index Terms
- Leveraging Crowdsourcing for the Thematic Annotation of the Qur'an
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Published In
April 2016
1094 pages
ISBN:9781450341448
- General Chairs:
- Jacqueline Bourdeau,
- Jim A. Hendler,
- Roger Nkambou Nkambou,
- Program Chairs:
- Ian Horrocks,
- Ben Y. Zhao
Copyright © 2016 Copyright is held by the owner/author(s).
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- IW3C2: International World Wide Web Conference Committee
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International World Wide Web Conferences Steering Committee
Republic and Canton of Geneva, Switzerland
Publication History
Published: 11 April 2016
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WWW '16
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- IW3C2
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WWW '16 Companion Paper Acceptance Rate 115 of 727 submissions, 16%;
Overall Acceptance Rate 1,899 of 8,196 submissions, 23%
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Cited By
View all- Dhinakaran KNedunchelian RBalasundaram A(2021)Crowdsourcing: Descriptive Study on Algorithms and Frameworks for PredictionArchives of Computational Methods in Engineering10.1007/s11831-021-09577-8Online publication date: 4-Apr-2021
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