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Contribution for newspaper or weekly magazine . 2016
https://doi.org/10.18653/v1/s1...
Article . 2016 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2019
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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SemEval-2016 Task 3: Community Question Answering

Authors: Nakov, Preslav; Màrquez, Lluís; Moschitti, Alessandro; Magdy, Walid; Mubarak, Hamdy; Freihat, Abed Alhakim; Glass, James; +1 Authors

SemEval-2016 Task 3: Community Question Answering

Abstract

This paper describes the SemEval--2016 Task 3 on Community Question Answering, which we offered in English and Arabic. For English, we had three subtasks: Question--Comment Similarity (subtask A), Question--Question Similarity (B), and Question--External Comment Similarity (C). For Arabic, we had another subtask: Rerank the correct answers for a new question (D). Eighteen teams participated in the task, submitting a total of 95 runs (38 primary and 57 contrastive) for the four subtasks. A variety of approaches and features were used by the participating systems to address the different subtasks, which are summarized in this paper. The best systems achieved an official score (MAP) of 79.19, 76.70, 55.41, and 45.83 in subtasks A, B, C, and D, respectively. These scores are significantly better than those for the baselines that we provided. For subtask A, the best system improved over the 2015 winner by 3 points absolute in terms of Accuracy.

community question answering, question-question similarity, question-comment similarity, answer reranking, English, Arabic. arXiv admin note: substantial text overlap with arXiv:1912.00730

Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, I.2.7, 68T50, Theoretical Computer Science; Computational Theory and Mathematics; Computer Science Applications1707 Computer Vision and Pattern Recognition, Computation and Language (cs.CL), Information Retrieval (cs.IR), Computer Science - Information Retrieval

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    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    74
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
74
Top 10%
Top 1%
Top 1%
Green