@inproceedings{mihaylova-etal-2016-finding,
title = "Finding Good Answers in Online Forums: Community Question Answering for {B}ulgarian",
author = "Mihaylova, Tsvetomila and
Koychev, Ivan and
Nakov, Preslav and
Nikolova, Ivelina",
booktitle = "Proceedings of the Second International Conference on Computational Linguistics in Bulgaria (CLIB 2016)",
month = sep,
year = "2016",
address = "Sofia, Bulgaria",
publisher = "Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences",
url = "https://aclanthology.org/2016.clib-1.7",
pages = "54--63",
abstract = "Community Question Answering (CQA) is a form of question answering that is getting increasingly popular as a research direction recently. Given a question posted in an online community forum and the thread of answers to it, a common formulation of the task is to rank automatically the answers, so that the good ones are ranked higher than the bad ones. Despite the vast research in CQA for English, very little attention has been paid to other languages. To bridge this gap, here we present our method for Community Question Answering in Bulgarian. We create annotated training and testing datasets for Bulgarian, and we further explore the applicability of machine translation for reusing English CQA data for building a Bulgarian system. The evaluation results show improvement over the baseline and can serve as a basis for further research.",
}
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<abstract>Community Question Answering (CQA) is a form of question answering that is getting increasingly popular as a research direction recently. Given a question posted in an online community forum and the thread of answers to it, a common formulation of the task is to rank automatically the answers, so that the good ones are ranked higher than the bad ones. Despite the vast research in CQA for English, very little attention has been paid to other languages. To bridge this gap, here we present our method for Community Question Answering in Bulgarian. We create annotated training and testing datasets for Bulgarian, and we further explore the applicability of machine translation for reusing English CQA data for building a Bulgarian system. The evaluation results show improvement over the baseline and can serve as a basis for further research.</abstract>
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%0 Conference Proceedings
%T Finding Good Answers in Online Forums: Community Question Answering for Bulgarian
%A Mihaylova, Tsvetomila
%A Koychev, Ivan
%A Nakov, Preslav
%A Nikolova, Ivelina
%S Proceedings of the Second International Conference on Computational Linguistics in Bulgaria (CLIB 2016)
%D 2016
%8 September
%I Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences
%C Sofia, Bulgaria
%F mihaylova-etal-2016-finding
%X Community Question Answering (CQA) is a form of question answering that is getting increasingly popular as a research direction recently. Given a question posted in an online community forum and the thread of answers to it, a common formulation of the task is to rank automatically the answers, so that the good ones are ranked higher than the bad ones. Despite the vast research in CQA for English, very little attention has been paid to other languages. To bridge this gap, here we present our method for Community Question Answering in Bulgarian. We create annotated training and testing datasets for Bulgarian, and we further explore the applicability of machine translation for reusing English CQA data for building a Bulgarian system. The evaluation results show improvement over the baseline and can serve as a basis for further research.
%U https://aclanthology.org/2016.clib-1.7
%P 54-63
Markdown (Informal)
[Finding Good Answers in Online Forums: Community Question Answering for Bulgarian](https://aclanthology.org/2016.clib-1.7) (Mihaylova et al., CLIB 2016)
ACL
- Tsvetomila Mihaylova, Ivan Koychev, Preslav Nakov, and Ivelina Nikolova. 2016. Finding Good Answers in Online Forums: Community Question Answering for Bulgarian. In Proceedings of the Second International Conference on Computational Linguistics in Bulgaria (CLIB 2016), pages 54–63, Sofia, Bulgaria. Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences.