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Conference Paper/Proceeding/Abstract 788 views

Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report

Anastasia Griva Orcid Logo, Denis Dennehy Orcid Logo

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society, Pages: 545 - 551

Swansea University Author: Denis Dennehy Orcid Logo

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DOI (Published version): 10.1007/978-3-030-85447-8_45

Published in: Responsible AI and Analytics for an Ethical and Inclusive Digitized Society
ISBN: 9783030854461 9783030854478
ISSN: 0302-9743 1611-3349
Published: Cham Springer International Publishing 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa59530
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title Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
spellingShingle Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
Denis Dennehy
title_short Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
title_full Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
title_fullStr Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
title_full_unstemmed Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
title_sort Mining Segmentation Patterns Using e-Commerce Retail Data: An Experience Report
author_id_str_mv ba782cbe94139075e5418dc9274e8304
author_id_fullname_str_mv ba782cbe94139075e5418dc9274e8304_***_Denis Dennehy
author Denis Dennehy
author2 Anastasia Griva
Denis Dennehy
format Conference Paper/Proceeding/Abstract
container_title Responsible AI and Analytics for an Ethical and Inclusive Digitized Society
container_start_page 545
publishDate 2021
institution Swansea University
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9783030854478
issn 0302-9743
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doi_str_mv 10.1007/978-3-030-85447-8_45
publisher Springer International Publishing
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published_date 2021-08-25T05:01:20Z
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