Semi-Supervised Soft K-Means Clustering of Life Insurance Questionnaire Responses

Biddle, R; Liu, S; Xu, G

Semi-Supervised Soft K-Means Clustering of Life Insurance Questionnaire Responses

Biddle, R Liu, S

Xu, G

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2018 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2018, 2018, pp. 30 - 31
Issue Date:: 2018-07-02

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Field	Value	Language
dc.contributor.author	Biddle, R	en_US
dc.contributor.author	Liu, S https://orcid.org/0000-0001-6062-6580	en_US
dc.contributor.author	Xu, G https://orcid.org/0000-0003-4493-6663	en_US
dc.date.available	2021-04-27T19:02:26Z
dc.date.issued	2018-07-02	en_US
dc.identifier.citation	Proceedings - 2018 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2018, 2018, pp. 30 - 31	en_US
dc.identifier.isbn	9781728102078	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133522
dc.description.abstract	© 2018 IEEE. The life insurance questionnaire is a large document containing responses in a mixture of structured and unstructured data. The unstructured data poses issues for the user, in the form of extra input effort, and the insurance company, in the form of interpretation and analysis. In this work, we aim to address these problems by proposing a semi-supervised framework for clustering responses into categories using vector space embedding of responses and soft k-means clustering. Our experiments show that our method achieves adequate results. The resulting category clusters from our method can be used for analysis and to replace free text input questions with structured questions in the questionnaire.	en_US
dc.relation.ispartof	Proceedings - 2018 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2018	en_US
dc.relation.isbasedon	10.1109/BESC.2018.8697227	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Semi-Supervised Soft K-Means Clustering of Life Insurance Questionnaire Responses	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. The life insurance questionnaire is a large document containing responses in a mixture of structured and unstructured data. The unstructured data poses issues for the user, in the form of extra input effort, and the insurance company, in the form of interpretation and analysis. In this work, we aim to address these problems by proposing a semi-supervised framework for clustering responses into categories using vector space embedding of responses and soft k-means clustering. Our experiments show that our method achieves adequate results. The resulting category clusters from our method can be used for analysis and to replace free text input questions with structured questions in the questionnaire.

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http://hdl.handle.net/10453/133522