Classification of opinion questions

Hongping Fu; Zhendong Niu; Chunxia Zhang; Lu Wang; Peng Jiang; Ji Zhang

doi:10.1007/978-3-642-36973-5_67

Classification of opinion questions

Hongping Fu, Zhendong Niu^*, Chunxia Zhang, Lu Wang, Peng Jiang, Ji Zhang

^*Corresponding author for this work

School of Computer Science and Technology

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

1 Citation (Scopus)

Abstract

With the increasing growth of opinions on news, services and so on, automatic opinion question answering aims at answering questions involving views of persons, and plays an important role in fields of sentiment analysis and information recommendation. One challenge is that opinion questions may contain different types of question focuses that affect answer extraction, such as holders, comparison and location. In this paper, we build a taxonomy of opinion questions, and propose a hierarchical classification technique to classify opinion questions according to our constructed taxonomy. This technique first uses Bayesian classifier and then employs an approach leveraging semantic similarities between questions. Experimental results show that our approach significantly improves performances over baseline and other related works.

Original language	English
Title of host publication	Advances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings
Pages	714-717
Number of pages	4
DOIs	https://doi.org/10.1007/978-3-642-36973-5_67
Publication status	Published - 2013
Event	35th European Conference on Information Retrieval, ECIR 2013 - Moscow, Russian Federation Duration: 24 Mar 2013 → 27 Mar 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7814 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	35th European Conference on Information Retrieval, ECIR 2013
Country/Territory	Russian Federation
City	Moscow
Period	24/03/13 → 27/03/13

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10.1007/978-3-642-36973-5_67

Cite this

Fu, H., Niu, Z., Zhang, C., Wang, L., Jiang, P., & Zhang, J. (2013). Classification of opinion questions. In Advances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings (pp. 714-717). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7814 LNCS). https://doi.org/10.1007/978-3-642-36973-5_67

@inproceedings{0fe12bab92974bd7ba41460d6547b9f2,

title = "Classification of opinion questions",

abstract = "With the increasing growth of opinions on news, services and so on, automatic opinion question answering aims at answering questions involving views of persons, and plays an important role in fields of sentiment analysis and information recommendation. One challenge is that opinion questions may contain different types of question focuses that affect answer extraction, such as holders, comparison and location. In this paper, we build a taxonomy of opinion questions, and propose a hierarchical classification technique to classify opinion questions according to our constructed taxonomy. This technique first uses Bayesian classifier and then employs an approach leveraging semantic similarities between questions. Experimental results show that our approach significantly improves performances over baseline and other related works.",

author = "Hongping Fu and Zhendong Niu and Chunxia Zhang and Lu Wang and Peng Jiang and Ji Zhang",

year = "2013",

doi = "10.1007/978-3-642-36973-5_67",

language = "English",

isbn = "9783642369728",

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

pages = "714--717",

booktitle = "Advances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings",

note = "35th European Conference on Information Retrieval, ECIR 2013 ; Conference date: 24-03-2013 Through 27-03-2013",

}

Fu, H, Niu, Z , Zhang, C, Wang, L, Jiang, P & Zhang, J 2013, Classification of opinion questions. in Advances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7814 LNCS, pp. 714-717, 35th European Conference on Information Retrieval, ECIR 2013, Moscow, Russian Federation, 24/03/13. https://doi.org/10.1007/978-3-642-36973-5_67

Classification of opinion questions. / Fu, Hongping; Niu, Zhendong ; Zhang, Chunxia et al.
Advances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings. 2013. p. 714-717 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7814 LNCS).

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

TY - GEN

T1 - Classification of opinion questions

AU - Fu, Hongping

AU - Niu, Zhendong

AU - Zhang, Chunxia

AU - Wang, Lu

AU - Jiang, Peng

AU - Zhang, Ji

PY - 2013

Y1 - 2013

N2 - With the increasing growth of opinions on news, services and so on, automatic opinion question answering aims at answering questions involving views of persons, and plays an important role in fields of sentiment analysis and information recommendation. One challenge is that opinion questions may contain different types of question focuses that affect answer extraction, such as holders, comparison and location. In this paper, we build a taxonomy of opinion questions, and propose a hierarchical classification technique to classify opinion questions according to our constructed taxonomy. This technique first uses Bayesian classifier and then employs an approach leveraging semantic similarities between questions. Experimental results show that our approach significantly improves performances over baseline and other related works.

AB - With the increasing growth of opinions on news, services and so on, automatic opinion question answering aims at answering questions involving views of persons, and plays an important role in fields of sentiment analysis and information recommendation. One challenge is that opinion questions may contain different types of question focuses that affect answer extraction, such as holders, comparison and location. In this paper, we build a taxonomy of opinion questions, and propose a hierarchical classification technique to classify opinion questions according to our constructed taxonomy. This technique first uses Bayesian classifier and then employs an approach leveraging semantic similarities between questions. Experimental results show that our approach significantly improves performances over baseline and other related works.

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DO - 10.1007/978-3-642-36973-5_67

M3 - Conference contribution

AN - SCOPUS:84875473725

SN - 9783642369728

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 714

EP - 717

BT - Advances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings

T2 - 35th European Conference on Information Retrieval, ECIR 2013

Y2 - 24 March 2013 through 27 March 2013

ER -

Fu H, Niu Z , Zhang C, Wang L, Jiang P, Zhang J. Classification of opinion questions. In Advances in Information Retrieval - 35th European Conference on IR Research, ECIR 2013, Proceedings. 2013. p. 714-717. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-36973-5_67

Classification of opinion questions

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