@inproceedings{galitsky-ilvovsky-2019-two,
title = "Two Discourse Tree - Based Approaches to Indexing Answers",
author = "Galitsky, Boris and
Ilvovsky, Dmitry",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
month = sep,
year = "2019",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://aclanthology.org/R19-1043",
doi = "10.26615/978-954-452-056-4_043",
pages = "367--372",
abstract = "We explore anatomy of answers with respect to which text fragments from an answer are worth matching with a question and which should not be matched. We apply the Rhetorical Structure Theory to build a discourse tree of an answer and select elementary discourse units that are suitable for indexing. Manual rules for selection of these discourse units as well as automated classification based on web search engine mining are evaluated con-cerning improving search accuracy. We form two sets of question-answer pairs for FAQ and community QA search domains and use them for evaluation of the proposed indexing methodology, which delivers up to 16 percent improvement in search recall.",
}
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%0 Conference Proceedings
%T Two Discourse Tree - Based Approaches to Indexing Answers
%A Galitsky, Boris
%A Ilvovsky, Dmitry
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F galitsky-ilvovsky-2019-two
%X We explore anatomy of answers with respect to which text fragments from an answer are worth matching with a question and which should not be matched. We apply the Rhetorical Structure Theory to build a discourse tree of an answer and select elementary discourse units that are suitable for indexing. Manual rules for selection of these discourse units as well as automated classification based on web search engine mining are evaluated con-cerning improving search accuracy. We form two sets of question-answer pairs for FAQ and community QA search domains and use them for evaluation of the proposed indexing methodology, which delivers up to 16 percent improvement in search recall.
%R 10.26615/978-954-452-056-4_043
%U https://aclanthology.org/R19-1043
%U https://doi.org/10.26615/978-954-452-056-4_043
%P 367-372
Markdown (Informal)
[Two Discourse Tree - Based Approaches to Indexing Answers](https://aclanthology.org/R19-1043) (Galitsky & Ilvovsky, RANLP 2019)
ACL