Domain specific grammar based classification for factoid questions

Alaa Mohasseb; Mohamed Bader-El-Den; Mihaela Cocea

doi:10.5220/0007958601770184

Domain specific grammar based classification for factoid questions

Alaa Mohasseb^*, Mohamed Bader-El-Den, Mihaela Cocea

^*Corresponding author for this work

School of Computing

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

128 Downloads (Pure)

Abstract

The process of classifying questions in any question answering systems is the first step in retrieving accurate answers. Factoid questions are considered the most challenging type of question to classify. In this paper, a framework has been adapted for question categorization and classification. The framework consists of three main features which are, grammatical features, domain-specific features, and grammatical patterns. These features help in preserving and utilizing the structure of the questions. Machine learning algorithms were used for the classification process in which experimental results show that these features helped in achieving a good level of accuracy compared with the state-of-art approaches.

Original language	English
Title of host publication	Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, 2019
Editors	Alessandro Bozzon, Francisco Domínguez Mayo, Joaquim Filipe
Publisher	SciTePress
Pages	177-184
Number of pages	8
ISBN (Print)	9789897583865
DOIs	https://doi.org/10.5220/0007958601770184
Publication status	Published - 18 Sept 2019
Event	15th International Conference on Web Information Systems and Technologies - Vienna University of Technology, Vienna, Austria Duration: 18 Sept 2019 → 20 Sept 2019 Conference number: 15 http://www.webist.org/Home.aspx

Conference

Conference	15th International Conference on Web Information Systems and Technologies
Abbreviated title	WEBIST
Country/Territory	Austria
City	Vienna
Period	18/09/19 → 20/09/19
Internet address	http://www.webist.org/Home.aspx

Keywords

information retrieval
question classification
machine learning
grammatical features

Access to Document

10.5220/0007958601770184

Domain Specific Grammar Based Classification For Factoid Questions
This is the accepted manuscript of Mohasseb, A.; Bader-El-Den, M. and Cocea, M. (2019). Domain Specific Grammar based Classification for Factoid Questions. In Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST, ISBN 978-989-758-386-5; ISSN 2184-3252, pages 177-184. DOI: 10.5220/0007958601770184.
Accepted author manuscript (Post-print), 139 KB

Cite this

@inproceedings{134019a8d51642fb8044c081bcc94e3f,

title = "Domain specific grammar based classification for factoid questions",

abstract = "The process of classifying questions in any question answering systems is the first step in retrieving accurate answers. Factoid questions are considered the most challenging type of question to classify. In this paper, a framework has been adapted for question categorization and classification. The framework consists of three main features which are, grammatical features, domain-specific features, and grammatical patterns. These features help in preserving and utilizing the structure of the questions. Machine learning algorithms were used for the classification process in which experimental results show that these features helped in achieving a good level of accuracy compared with the state-of-art approaches.",

keywords = "information retrieval, question classification, machine learning, grammatical features",

author = "Alaa Mohasseb and Mohamed Bader-El-Den and Mihaela Cocea",

year = "2019",

month = sep,

day = "18",

doi = "10.5220/0007958601770184",

language = "English",

isbn = "9789897583865",

pages = "177--184",

editor = "Alessandro Bozzon and Mayo, {Francisco Dom{\'i}nguez} and Joaquim Filipe",

booktitle = "Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, 2019",

publisher = "SciTePress",

note = "15th International Conference on Web Information Systems and Technologies, WEBIST ; Conference date: 18-09-2019 Through 20-09-2019",

url = "http://www.webist.org/Home.aspx",

}

Mohasseb, A , Bader-El-Den, M & Cocea, M 2019, Domain specific grammar based classification for factoid questions. in A Bozzon, FD Mayo & J Filipe (eds), Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, 2019. SciTePress, pp. 177-184, 15th International Conference on Web Information Systems and Technologies, Vienna, Austria, 18/09/19. https://doi.org/10.5220/0007958601770184

Domain specific grammar based classification for factoid questions. / Mohasseb, Alaa ; Bader-El-Den, Mohamed ; Cocea, Mihaela.
Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, 2019. ed. / Alessandro Bozzon; Francisco Domínguez Mayo; Joaquim Filipe. SciTePress, 2019. p. 177-184.

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

TY - GEN

T1 - Domain specific grammar based classification for factoid questions

AU - Mohasseb, Alaa

AU - Bader-El-Den, Mohamed

AU - Cocea, Mihaela

N1 - Conference code: 15

PY - 2019/9/18

Y1 - 2019/9/18

N2 - The process of classifying questions in any question answering systems is the first step in retrieving accurate answers. Factoid questions are considered the most challenging type of question to classify. In this paper, a framework has been adapted for question categorization and classification. The framework consists of three main features which are, grammatical features, domain-specific features, and grammatical patterns. These features help in preserving and utilizing the structure of the questions. Machine learning algorithms were used for the classification process in which experimental results show that these features helped in achieving a good level of accuracy compared with the state-of-art approaches.

AB - The process of classifying questions in any question answering systems is the first step in retrieving accurate answers. Factoid questions are considered the most challenging type of question to classify. In this paper, a framework has been adapted for question categorization and classification. The framework consists of three main features which are, grammatical features, domain-specific features, and grammatical patterns. These features help in preserving and utilizing the structure of the questions. Machine learning algorithms were used for the classification process in which experimental results show that these features helped in achieving a good level of accuracy compared with the state-of-art approaches.

KW - information retrieval

KW - question classification

KW - machine learning

KW - grammatical features

UR - http://www.webist.org/

UR - https://link.springer.com/conference/webist

U2 - 10.5220/0007958601770184

DO - 10.5220/0007958601770184

M3 - Conference contribution

SN - 9789897583865

SP - 177

EP - 184

BT - Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, 2019

A2 - Bozzon, Alessandro

A2 - Mayo, Francisco Domínguez

A2 - Filipe, Joaquim

PB - SciTePress

T2 - 15th International Conference on Web Information Systems and Technologies

Y2 - 18 September 2019 through 20 September 2019

ER -

Domain specific grammar based classification for factoid questions

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this