An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation

Sultan Ceren Öner; Başar Öztayşi

doi:10.1007/978-3-319-66827-7_6

An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation

Sultan Ceren Öner^*, Başar Öztayşi

^*Corresponding author for this work

Department of Industrial Engineering

Istanbul Technical University

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

4 Citations (Scopus)

Abstract

Because of the irrepressible growth in information technologies and telecommunication infrastructure especially for mobile devices, people are more disposed to search proper products and find out attractive offers with lower prices. In order to reach potential customers, companies deal with offering personalized messages including special promotions and discounts. In this respect, recommender systems have begun to use as one of the essential tools for making appropriate selections considering diversified conditions and personal preferences. On the other hand, users’ preferences could not be easily determined or predicted in some cases, as seen in visiting prediction of mobile users. Thus, the use of location based service applications enable the determination of users visiting patterns, except making predictions. In this study, an interval valued hesitant fuzzy clustering approach is adapted based on location similarity and fuzzy c means clustering is applied for user segmentation. After that, matching location groups and user segments is provided the representation of user visiting tendency. By using this approach, advertisers will be able to handle their advertisements considering location similarities and user groups that helps the implementation of personalized advertising recommender systems.

Original language	English
Title of host publication	Advances in Fuzzy Logic and Technology 2017 - Proceedings of
Subtitle of host publication	EUSFLAT-2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, IWIFSGN’2017 – The 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets
Editors	Krassimir T. Atanassov, Maciej Krawczak, Janusz Kacprzyk, Eulalia Szmidt, Slawomir Zadrozny, Maciej Krawczak
Publisher	Springer Verlag
Pages	56-70
Number of pages	15
ISBN (Print)	9783319668260
DOIs	https://doi.org/10.1007/978-3-319-66827-7_6
Publication status	Published - 2018
Event	Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017 - Warsaw, Poland Duration: 11 Sept 2017 → 15 Sept 2017

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	643
ISSN (Print)	2194-5357

Conference

Conference	Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017
Country/Territory	Poland
City	Warsaw
Period	11/09/17 → 15/09/17

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG.

Keywords

Hesitant fuzzy clustering
Interval valued hesitant fuzzy clustering
Location similarity
Segmentation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-66827-7_6

Cite this

Öner, S. C., & Öztayşi, B. (2018). An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation. In K. T. Atanassov, M. Krawczak, J. Kacprzyk, E. Szmidt, S. Zadrozny, & M. Krawczak (Eds.), Advances in Fuzzy Logic and Technology 2017 - Proceedings of: EUSFLAT-2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, IWIFSGN’2017 – The 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets (pp. 56-70). (Advances in Intelligent Systems and Computing; Vol. 643). Springer Verlag. https://doi.org/10.1007/978-3-319-66827-7_6

Öner, Sultan Ceren ; Öztayşi, Başar. / An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation. Advances in Fuzzy Logic and Technology 2017 - Proceedings of: EUSFLAT-2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, IWIFSGN’2017 – The 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets. editor / Krassimir T. Atanassov ; Maciej Krawczak ; Janusz Kacprzyk ; Eulalia Szmidt ; Slawomir Zadrozny ; Maciej Krawczak. Springer Verlag, 2018. pp. 56-70 (Advances in Intelligent Systems and Computing).

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title = "An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation",

abstract = "Because of the irrepressible growth in information technologies and telecommunication infrastructure especially for mobile devices, people are more disposed to search proper products and find out attractive offers with lower prices. In order to reach potential customers, companies deal with offering personalized messages including special promotions and discounts. In this respect, recommender systems have begun to use as one of the essential tools for making appropriate selections considering diversified conditions and personal preferences. On the other hand, users{\textquoteright} preferences could not be easily determined or predicted in some cases, as seen in visiting prediction of mobile users. Thus, the use of location based service applications enable the determination of users visiting patterns, except making predictions. In this study, an interval valued hesitant fuzzy clustering approach is adapted based on location similarity and fuzzy c means clustering is applied for user segmentation. After that, matching location groups and user segments is provided the representation of user visiting tendency. By using this approach, advertisers will be able to handle their advertisements considering location similarities and user groups that helps the implementation of personalized advertising recommender systems.",

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author = "{\"O}ner, {Sultan Ceren} and Ba{\c s}ar {\"O}ztay{\c s}i",

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Öner, SC & Öztayşi, B 2018, An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation. in KT Atanassov, M Krawczak, J Kacprzyk, E Szmidt, S Zadrozny & M Krawczak (eds), Advances in Fuzzy Logic and Technology 2017 - Proceedings of: EUSFLAT-2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, IWIFSGN’2017 – The 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets. Advances in Intelligent Systems and Computing, vol. 643, Springer Verlag, pp. 56-70, Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017, Warsaw, Poland, 11/09/17. https://doi.org/10.1007/978-3-319-66827-7_6

An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation. / Öner, Sultan Ceren; Öztayşi, Başar.
Advances in Fuzzy Logic and Technology 2017 - Proceedings of: EUSFLAT-2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, IWIFSGN’2017 – The 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets. ed. / Krassimir T. Atanassov; Maciej Krawczak; Janusz Kacprzyk; Eulalia Szmidt; Slawomir Zadrozny; Maciej Krawczak. Springer Verlag, 2018. p. 56-70 (Advances in Intelligent Systems and Computing; Vol. 643).

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

TY - GEN

T1 - An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation

AU - Öner, Sultan Ceren

AU - Öztayşi, Başar

PY - 2018

Y1 - 2018

N2 - Because of the irrepressible growth in information technologies and telecommunication infrastructure especially for mobile devices, people are more disposed to search proper products and find out attractive offers with lower prices. In order to reach potential customers, companies deal with offering personalized messages including special promotions and discounts. In this respect, recommender systems have begun to use as one of the essential tools for making appropriate selections considering diversified conditions and personal preferences. On the other hand, users’ preferences could not be easily determined or predicted in some cases, as seen in visiting prediction of mobile users. Thus, the use of location based service applications enable the determination of users visiting patterns, except making predictions. In this study, an interval valued hesitant fuzzy clustering approach is adapted based on location similarity and fuzzy c means clustering is applied for user segmentation. After that, matching location groups and user segments is provided the representation of user visiting tendency. By using this approach, advertisers will be able to handle their advertisements considering location similarities and user groups that helps the implementation of personalized advertising recommender systems.

AB - Because of the irrepressible growth in information technologies and telecommunication infrastructure especially for mobile devices, people are more disposed to search proper products and find out attractive offers with lower prices. In order to reach potential customers, companies deal with offering personalized messages including special promotions and discounts. In this respect, recommender systems have begun to use as one of the essential tools for making appropriate selections considering diversified conditions and personal preferences. On the other hand, users’ preferences could not be easily determined or predicted in some cases, as seen in visiting prediction of mobile users. Thus, the use of location based service applications enable the determination of users visiting patterns, except making predictions. In this study, an interval valued hesitant fuzzy clustering approach is adapted based on location similarity and fuzzy c means clustering is applied for user segmentation. After that, matching location groups and user segments is provided the representation of user visiting tendency. By using this approach, advertisers will be able to handle their advertisements considering location similarities and user groups that helps the implementation of personalized advertising recommender systems.

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KW - Interval valued hesitant fuzzy clustering

KW - Location similarity

KW - Segmentation

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DO - 10.1007/978-3-319-66827-7_6

M3 - Conference contribution

AN - SCOPUS:85029435612

SN - 9783319668260

T3 - Advances in Intelligent Systems and Computing

SP - 56

EP - 70

BT - Advances in Fuzzy Logic and Technology 2017 - Proceedings of

A2 - Atanassov, Krassimir T.

A2 - Krawczak, Maciej

A2 - Kacprzyk, Janusz

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A2 - Zadrozny, Slawomir

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PB - Springer Verlag

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Y2 - 11 September 2017 through 15 September 2017

ER -

Öner SC, Öztayşi B. An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation. In Atanassov KT, Krawczak M, Kacprzyk J, Szmidt E, Zadrozny S, Krawczak M, editors, Advances in Fuzzy Logic and Technology 2017 - Proceedings of: EUSFLAT-2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, IWIFSGN’2017 – The 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets. Springer Verlag. 2018. p. 56-70. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-66827-7_6

An interval valued hesitant fuzzy clustering approach for location clustering and customer segmentation

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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Cite this