Identifying unclear questions in community question answering websites

Jan Trienes; Krisztian Balog

doi:10.1007/978-3-030-15712-8_18

Identifying unclear questions in community question answering websites

Jan Trienes^*, Krisztian Balog

^*Corresponding author for this work

Datamanagement & Biometrics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

23 Citations (Scopus)

27 Downloads (Pure)

Abstract

Thousands of complex natural language questions are submitted to community question answering websites on a daily basis, rendering them as one of the most important information sources these days. However, oftentimes submitted questions are unclear and cannot be answered without further clarification questions by expert community members. This study is the first to investigate the complex task of classifying a question as clear or unclear, i.e., if it requires further clarification. We construct a novel dataset and propose a classification approach that is based on the notion of similar questions. This approach is compared to state-of-the-art text classification baselines. Our main finding is that the similar questions approach is a viable alternative that can be used as a stepping stone towards the development of supportive user interfaces for question formulation.

Original language	English
Title of host publication	Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings
Editors	Benno Stein, Philipp Mayr, Leif Azzopardi, Djoerd Hiemstra, Norbert Fuhr, Claudia Hauff
Publisher	Springer
Pages	276-289
Number of pages	14
ISBN (Print)	9783030157111
DOIs	https://doi.org/10.1007/978-3-030-15712-8_18
Publication status	Published - 7 Apr 2019
Event	41st European Conference on Information Retrieval, ECIR 2019 - Cologne, Germany Duration: 14 Apr 2019 → 18 Apr 2019 Conference number: 41 http://ecir2019.org/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11437 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	41st European Conference on Information Retrieval, ECIR 2019
Abbreviated title	ECIR 2019
Country/Territory	Germany
City	Cologne
Period	14/04/19 → 18/04/19
Internet address	http://ecir2019.org/

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10.1007/978-3-030-15712-8_18

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Trienes, J., & Balog, K. (2019). Identifying unclear questions in community question answering websites. In B. Stein, P. Mayr, L. Azzopardi, D. Hiemstra, N. Fuhr, & C. Hauff (Eds.), Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings (pp. 276-289). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11437 LNCS). Springer. https://doi.org/10.1007/978-3-030-15712-8_18

Trienes, Jan ; Balog, Krisztian. / Identifying unclear questions in community question answering websites. Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. editor / Benno Stein ; Philipp Mayr ; Leif Azzopardi ; Djoerd Hiemstra ; Norbert Fuhr ; Claudia Hauff. Springer, 2019. pp. 276-289 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Identifying unclear questions in community question answering websites",

abstract = "Thousands of complex natural language questions are submitted to community question answering websites on a daily basis, rendering them as one of the most important information sources these days. However, oftentimes submitted questions are unclear and cannot be answered without further clarification questions by expert community members. This study is the first to investigate the complex task of classifying a question as clear or unclear, i.e., if it requires further clarification. We construct a novel dataset and propose a classification approach that is based on the notion of similar questions. This approach is compared to state-of-the-art text classification baselines. Our main finding is that the similar questions approach is a viable alternative that can be used as a stepping stone towards the development of supportive user interfaces for question formulation.",

author = "Jan Trienes and Krisztian Balog",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Trienes, J & Balog, K 2019, Identifying unclear questions in community question answering websites. in B Stein, P Mayr, L Azzopardi, D Hiemstra, N Fuhr & C Hauff (eds), Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11437 LNCS, Springer, pp. 276-289, 41st European Conference on Information Retrieval, ECIR 2019, Cologne, Germany, 14/04/19. https://doi.org/10.1007/978-3-030-15712-8_18

Identifying unclear questions in community question answering websites. / Trienes, Jan; Balog, Krisztian.
Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. ed. / Benno Stein; Philipp Mayr; Leif Azzopardi; Djoerd Hiemstra; Norbert Fuhr; Claudia Hauff. Springer, 2019. p. 276-289 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11437 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - Thousands of complex natural language questions are submitted to community question answering websites on a daily basis, rendering them as one of the most important information sources these days. However, oftentimes submitted questions are unclear and cannot be answered without further clarification questions by expert community members. This study is the first to investigate the complex task of classifying a question as clear or unclear, i.e., if it requires further clarification. We construct a novel dataset and propose a classification approach that is based on the notion of similar questions. This approach is compared to state-of-the-art text classification baselines. Our main finding is that the similar questions approach is a viable alternative that can be used as a stepping stone towards the development of supportive user interfaces for question formulation.

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Trienes J, Balog K. Identifying unclear questions in community question answering websites. In Stein B, Mayr P, Azzopardi L, Hiemstra D, Fuhr N, Hauff C, editors, Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. Springer. 2019. p. 276-289. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-15712-8_18

Identifying unclear questions in community question answering websites

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