المؤسسة التعليمية |
The University Of Sheffield |
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مجال التميز |
تميز دراسي وبحثي |
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البحوث المنشورة |
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البحث (1): |
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عنوان البحث: |
Semantic Web And Human Computation: The Status Of An Emerging Field |
رابط إلى البحث: |
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تاريخ النشر: |
12 April 2018 |
موجز عن البحث: |
This editorial paper introduces a special issue that solicited papers at the intersection of Semantic Web and Human Computation research. Research in that inter-disciplinary space dates back a decade, and has been acknowledged as a research line of its own by a seminal research manifesto published in 2015. But where do we stand in 2018? How did this research line evolve during the last decade? How do the papers in this special issue align with the main lines of work of the community? In this editorial we inspect and reflect on the evolution of research at the intersection of Semantic Web and Human Computation. We use a methodology based on Systematic Mapping Studies to collect quantitative bibliographic data which we analyze through the lens of research topics envisioned by the research manifesto to characterize the evolution of research in this area, thus providing a context for introducing the papers of this special issue. We found evidences of a thriving research field; while steadily maturing, the field offers a number of open research opportunities for work where Semantic Web best practices and techniques are applied to support and improve the state-of-the-art in Human Computation, but also for work that exploits the strength of both areas to address scientifically and societally relevant issues. |
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المؤتمرات العلمية: |
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المؤتمر (1): |
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عنوان المؤتمر: |
The Fourth AAAI Conference On Human Computation And Crowdsourcing (HCOMP 2016) |
تاريخ الإنعقاد: |
30th October-3rd November 2016 |
مكان الإنعقاد: |
Austin, TX, USA |
طبيعة المشاركة: |
Oral presentation |
عنوان المشاركة: |
The Effect Of Class Imbalance And Order On Crowdsourced Relevance Judgments |
ملخص المشاركة: |
In this paper we study the effect on crowd worker efficiency and effectiveness of the dominance of one class in the data they process. We aim at understanding if there is any positive or negative bias in workers seeing many negative examples in the identification of positive labels. To test our hypothesis, we design an experiment where crowd workers are asked to judge the relevance of documents presented in different orders. Our findings indicate that there is a significant improvement in the quality of relevance judgements when presenting relevant results before the non-relevant ones. |
الرابط: |
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المؤتمر (2): |
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عنوان المؤتمر: |
The Sixth AAAI Conference On Human Computation And Crowdsourcing (HCOMP 2018) |
تاريخ الإنعقاد: |
05-08 July 2018 |
مكان الإنعقاد: |
Zurich, Switzerland |
طبيعة المشاركة: |
Oral presentation |
عنوان المشاركة: |
Investigating Stability And Reliability Of Crowdsourcing Output |
ملخص المشاركة: |
This research proposes to investigate the reliability of the output of crowdsourcing platforms and its consistency over time. We study the effect of design interface and instructions and identify critical differences between two platforms that have been used widely in research and data collection and evaluation. Our findings will help to uncover data reliability problems and to propose changes in crowdsourcing platforms that can mitigate the inconsistencies of human contributions. |
الرابط: |
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رحاب كمال محمد صالح قاروت
دكتوراه
العلوم والتقنية
University of Sheffield