Utility-based data mining: An anthropometric case study

One of the most important challenges for the apparel industry is to produce garments that fit the population properly. In order to achieve this objective, it is crucial to understand the typical profile of consumer's bodies. In this work, we aim to identify the typical consumer from the virtual...

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Main Author: Pena, Isis
Format: Others
Language:en
Published: University of Ottawa (Canada) 2013
Subjects:
Online Access:http://hdl.handle.net/10393/27723
http://dx.doi.org/10.20381/ruor-18873
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spelling ndltd-uottawa.ca-oai-ruor.uottawa.ca-10393-277232018-01-05T19:07:40Z Utility-based data mining: An anthropometric case study Pena, Isis Computer Science. One of the most important challenges for the apparel industry is to produce garments that fit the population properly. In order to achieve this objective, it is crucial to understand the typical profile of consumer's bodies. In this work, we aim to identify the typical consumer from the virtual tailor's perspective. To this end, we perform clustering analysis on anthropometric and 3-D data to group the population into clothing sizes. Next, we perform multi-view relational classification to analyze the interplay of different body measurements within each size. In this study, we analyze three different populations as contained in the CAESAR(TM) database, namely, the American, the Italian and the Dutch populations. Throughout this study, we follow a utility-based data mining approach. The goal of utility-base data mining is to consider all utility aspects of the mining process and to thus maximize the utility of the entire process. In order to address this issue, we engage in dimension reduction techniques to find a smaller set of body measurement that reduces the cost and improves the performance of the mining process. We also apply objective interestingness measures in our analysis of demographic data, to improve the quality of the results and reduce the time and search space of the mining process. The analysis of demographic data allows us to better understand the demographic nature of potential customers, in order to target subgroups of potential customers better. 2013-11-07T19:02:27Z 2013-11-07T19:02:27Z 2008 2008 Thesis Source: Masters Abstracts International, Volume: 47-05, page: 2936. http://hdl.handle.net/10393/27723 http://dx.doi.org/10.20381/ruor-18873 en 133 p. University of Ottawa (Canada)
collection NDLTD
language en
format Others
sources NDLTD
topic Computer Science.
spellingShingle Computer Science.
Pena, Isis
Utility-based data mining: An anthropometric case study
description One of the most important challenges for the apparel industry is to produce garments that fit the population properly. In order to achieve this objective, it is crucial to understand the typical profile of consumer's bodies. In this work, we aim to identify the typical consumer from the virtual tailor's perspective. To this end, we perform clustering analysis on anthropometric and 3-D data to group the population into clothing sizes. Next, we perform multi-view relational classification to analyze the interplay of different body measurements within each size. In this study, we analyze three different populations as contained in the CAESAR(TM) database, namely, the American, the Italian and the Dutch populations. Throughout this study, we follow a utility-based data mining approach. The goal of utility-base data mining is to consider all utility aspects of the mining process and to thus maximize the utility of the entire process. In order to address this issue, we engage in dimension reduction techniques to find a smaller set of body measurement that reduces the cost and improves the performance of the mining process. We also apply objective interestingness measures in our analysis of demographic data, to improve the quality of the results and reduce the time and search space of the mining process. The analysis of demographic data allows us to better understand the demographic nature of potential customers, in order to target subgroups of potential customers better.
author Pena, Isis
author_facet Pena, Isis
author_sort Pena, Isis
title Utility-based data mining: An anthropometric case study
title_short Utility-based data mining: An anthropometric case study
title_full Utility-based data mining: An anthropometric case study
title_fullStr Utility-based data mining: An anthropometric case study
title_full_unstemmed Utility-based data mining: An anthropometric case study
title_sort utility-based data mining: an anthropometric case study
publisher University of Ottawa (Canada)
publishDate 2013
url http://hdl.handle.net/10393/27723
http://dx.doi.org/10.20381/ruor-18873
work_keys_str_mv AT penaisis utilitybaseddataminingananthropometriccasestudy
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