A hybrid model for migrating customer segmentation with missing attributes

Ma, J; Lin, H; Lu, J; Zhang, G

A hybrid model for migrating customer segmentation with missing attributes

Ma, J

Lin, H Lu, J

Zhang, G

Permalink

Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013, 2013, pp. 825 - 830
Issue Date:: 2013-10-31

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (516.94 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Ma, J https://orcid.org/0000-0002-4195-7760	en_US
dc.contributor.author	Lin, H	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.date.issued	2013-10-31	en_US
dc.identifier.citation	Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013, 2013, pp. 825 - 830	en_US
dc.identifier.isbn	9781479903474	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28037
dc.description.abstract	Due to missing attributes in an enterprise's database, migrating customer segmentation results from external dataset to enterprise database in difficult. In this paper, a hybrid model, called HMCS model, is presented. This model artificially generates values of missing attributes based on external dataset and populates them to enterprise database. Based on this model, an application in a telecom application is reported. Application indicates the presented model can produce acceptable segmentation results on the enterprise dataset which is with missing attributes. © 2013 IEEE.	en_US
dc.relation.ispartof	Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting, IFSA/NAFIPS 2013	en_US
dc.relation.isbasedon	10.1109/IFSA-NAFIPS.2013.6608507	en_US
dc.title	A hybrid model for migrating customer segmentation with missing attributes	en_US
dc.type	Conference Proceeding
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
dc.location.activity	Edmonton, Canada	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 - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

Due to missing attributes in an enterprise's database, migrating customer segmentation results from external dataset to enterprise database in difficult. In this paper, a hybrid model, called HMCS model, is presented. This model artificially generates values of missing attributes based on external dataset and populates them to enterprise database. Based on this model, an application in a telecom application is reported. Application indicates the presented model can produce acceptable segmentation results on the enterprise dataset which is with missing attributes. © 2013 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/28037