A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph

Patrik Bansky; Elspeth Edelstein; Jeff Z. Pan; Adam Wyner

doi:10.1007/978-3-030-41407-8_15

A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph

Patrik Bansky, Elspeth Edelstein, Jeff Z. Pan, Adam Wyner

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

Abstract

In the paper we propose a dynamic and informative solutionto an intelligent survey system that is based on knowledge graph. To illustrate our proposal, we focus on ordering the questions of the questionnaire component by their acceptance, along with conditional triggers that further customise participants’ experience, making the system dynamic. Evaluation of the system shows that the dynamic component can be beneficial in terms of lowering the number of questions asked and improving the quality of data, allowing more informative data to be collected in a survey of equivalent length. Fine-grained analysis allows assessment of the interaction of specific variables, as well as of individual respondents rather than just global results. The paper explores and evaluates two algorithms for the presentation of survey questions, leading to additional insights about how to improve the system.

Original language	English
Title of host publication	Semantic Technology
Subtitle of host publication	9th Joint International Conference, JIST 2019, Hangzhou, China, November 25–27, 2019, Proceedings
Editors	Xin Wang, Francesca Alessandra Lisi, Guohui Xiao, Elena Botoeva
Place of Publication	Cham
Publisher	Springer
Pages	226-241
Number of pages	16
ISBN (Electronic)	978-3-030-41407-8
ISBN (Print)	978-3-030-41406-1
DOIs	https://doi.org/10.1007/978-3-030-41407-8_15
Publication status	Published - 14 Feb 2020
Event	The 9th Joint International Semantic Technology Conference - Hangzhou, China Duration: 25 Nov 2019 → 27 Nov 2019 http://jist2019.openkg.cn/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer, Cham
Volume	12032
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	The 9th Joint International Semantic Technology Conference
Abbreviated title	JIST 2019
Country/Territory	China
City	Hangzhou
Period	25/11/19 → 27/11/19
Internet address	http://jist2019.openkg.cn/

Keywords / Materials (for Non-textual outputs)

Commonsense knowledge graph
Visual relationship detection
Visual Genome

Access to Document

10.1007/978-3-030-41407-8_15Licence: All Rights Reserved

https://link.springer.com/chapter/10.1007/978-3-030-41407-8_15Licence: All Rights Reserved

Cite this

Bansky, P., Edelstein, E., Pan, J. Z., & Wyner, A. (2020). A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph. In X. Wang, F. A. Lisi, G. Xiao, & E. Botoeva (Eds.), Semantic Technology: 9th Joint International Conference, JIST 2019, Hangzhou, China, November 25–27, 2019, Proceedings (pp. 226-241). (Lecture Notes in Computer Science ; Vol. 12032). Springer. https://doi.org/10.1007/978-3-030-41407-8_15

Bansky, Patrik ; Edelstein, Elspeth ; Pan, Jeff Z. et al. / A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph. Semantic Technology: 9th Joint International Conference, JIST 2019, Hangzhou, China, November 25–27, 2019, Proceedings. editor / Xin Wang ; Francesca Alessandra Lisi ; Guohui Xiao ; Elena Botoeva. Cham : Springer, 2020. pp. 226-241 (Lecture Notes in Computer Science ).

@inproceedings{1edd981dd92d4c9d868f638dc22e33c9,

title = "A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph",

abstract = "In the paper we propose a dynamic and informative solutionto an intelligent survey system that is based on knowledge graph. To illustrate our proposal, we focus on ordering the questions of the questionnaire component by their acceptance, along with conditional triggers that further customise participants{\textquoteright} experience, making the system dynamic. Evaluation of the system shows that the dynamic component can be beneficial in terms of lowering the number of questions asked and improving the quality of data, allowing more informative data to be collected in a survey of equivalent length. Fine-grained analysis allows assessment of the interaction of specific variables, as well as of individual respondents rather than just global results. The paper explores and evaluates two algorithms for the presentation of survey questions, leading to additional insights about how to improve the system.",

keywords = "Commonsense knowledge graph, Visual relationship detection, Visual Genome",

author = "Patrik Bansky and Elspeth Edelstein and Pan, {Jeff Z.} and Adam Wyner",

year = "2020",

month = feb,

day = "14",

doi = "10.1007/978-3-030-41407-8_15",

language = "English",

isbn = "978-3-030-41406-1",

series = "Lecture Notes in Computer Science ",

publisher = "Springer",

pages = "226--241",

editor = "Xin Wang and Lisi, {Francesca Alessandra} and Guohui Xiao and Elena Botoeva",

booktitle = "Semantic Technology",

address = "United Kingdom",

note = "The 9th Joint International Semantic Technology Conference , JIST 2019 ; Conference date: 25-11-2019 Through 27-11-2019",

url = "http://jist2019.openkg.cn/",

}

Bansky, P, Edelstein, E, Pan, JZ & Wyner, A 2020, A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph. in X Wang, FA Lisi, G Xiao & E Botoeva (eds), Semantic Technology: 9th Joint International Conference, JIST 2019, Hangzhou, China, November 25–27, 2019, Proceedings. Lecture Notes in Computer Science , vol. 12032, Springer, Cham, pp. 226-241, The 9th Joint International Semantic Technology Conference , Hangzhou, China, 25/11/19. https://doi.org/10.1007/978-3-030-41407-8_15

A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph. / Bansky, Patrik; Edelstein, Elspeth; Pan, Jeff Z. et al.
Semantic Technology: 9th Joint International Conference, JIST 2019, Hangzhou, China, November 25–27, 2019, Proceedings. ed. / Xin Wang; Francesca Alessandra Lisi; Guohui Xiao; Elena Botoeva. Cham: Springer, 2020. p. 226-241 (Lecture Notes in Computer Science ; Vol. 12032).

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

TY - GEN

T1 - A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph

AU - Bansky, Patrik

AU - Edelstein, Elspeth

AU - Pan, Jeff Z.

AU - Wyner, Adam

PY - 2020/2/14

Y1 - 2020/2/14

N2 - In the paper we propose a dynamic and informative solutionto an intelligent survey system that is based on knowledge graph. To illustrate our proposal, we focus on ordering the questions of the questionnaire component by their acceptance, along with conditional triggers that further customise participants’ experience, making the system dynamic. Evaluation of the system shows that the dynamic component can be beneficial in terms of lowering the number of questions asked and improving the quality of data, allowing more informative data to be collected in a survey of equivalent length. Fine-grained analysis allows assessment of the interaction of specific variables, as well as of individual respondents rather than just global results. The paper explores and evaluates two algorithms for the presentation of survey questions, leading to additional insights about how to improve the system.

AB - In the paper we propose a dynamic and informative solutionto an intelligent survey system that is based on knowledge graph. To illustrate our proposal, we focus on ordering the questions of the questionnaire component by their acceptance, along with conditional triggers that further customise participants’ experience, making the system dynamic. Evaluation of the system shows that the dynamic component can be beneficial in terms of lowering the number of questions asked and improving the quality of data, allowing more informative data to be collected in a survey of equivalent length. Fine-grained analysis allows assessment of the interaction of specific variables, as well as of individual respondents rather than just global results. The paper explores and evaluates two algorithms for the presentation of survey questions, leading to additional insights about how to improve the system.

KW - Commonsense knowledge graph

KW - Visual relationship detection

KW - Visual Genome

U2 - 10.1007/978-3-030-41407-8_15

DO - 10.1007/978-3-030-41407-8_15

M3 - Conference contribution

SN - 978-3-030-41406-1

T3 - Lecture Notes in Computer Science

SP - 226

EP - 241

BT - Semantic Technology

A2 - Wang, Xin

A2 - Lisi, Francesca Alessandra

A2 - Xiao, Guohui

A2 - Botoeva, Elena

PB - Springer

CY - Cham

T2 - The 9th Joint International Semantic Technology Conference

Y2 - 25 November 2019 through 27 November 2019

ER -

Bansky P, Edelstein E, Pan JZ, Wyner A. A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph. In Wang X, Lisi FA, Xiao G, Botoeva E, editors, Semantic Technology: 9th Joint International Conference, JIST 2019, Hangzhou, China, November 25–27, 2019, Proceedings. Cham: Springer. 2020. p. 226-241. (Lecture Notes in Computer Science ). doi: 10.1007/978-3-030-41407-8_15

A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph

Abstract

Publication series

Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

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Cite this