MBTI-based collaborative recommendation system: A case study of Webtoon contents

Myeong Yeon Yi; O. Joun Lee; Jason J. Jung

doi:10.1007/978-3-319-29236-6_11

MBTI-based collaborative recommendation system: A case study of Webtoon contents

Myeong Yeon Yi, O. Joun Lee, Jason J. Jung

Department of Artificial Intelligence

Chung-Ang University

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

6 Scopus citations

Abstract

A large number of Webtoon contents has caused difficulties on finding relevant Webtoons for users. Thereby, an efficient recommendation services are needed. However, since the existing recommendation method (e.g. collaborative filtering) has two fundamental problems: (i.e., data sparsity and scalability problem), it has difficulties with reflecting users’ personality. In this paper, we propose the MBTI-CF method to solve these problems and to involve users’ personality by building personality-based neighborhood using MBTI. In order to verify the efficiency of the proposed method, we conducted statistical testing by user survey (anonymous users have rated set of the pre-selected Webtoon contents). Three experimental results have shown that MBTI-CF provides improvement in terms of the data sparsity problem and the scalability problem and offers more stable performance.

Original language	English
Title of host publication	Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers
Editors	Phan Cong Vinh, Vangalur Alagar
Publisher	Springer Verlag
Pages	101-110
Number of pages	10
ISBN (Print)	9783319292359
DOIs	https://doi.org/10.1007/978-3-319-29236-6_11
State	Published - 2016
Event	4th International Conference on Context-Aware Systems and Applications, ICCASA 2015 - Vung Tau, Viet Nam Duration: 26 Nov 2015 → 27 Nov 2015

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	165
ISSN (Print)	1867-8211

Conference

Conference	4th International Conference on Context-Aware Systems and Applications, ICCASA 2015
Country/Territory	Viet Nam
City	Vung Tau
Period	26/11/15 → 27/11/15

Bibliographical note

Funding Information:
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP (Institute for Information & communications Technology Promotion). Also, this work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154).

Publisher Copyright:
© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

Keywords

Collaborative filtering
MBTI (Myers-Briggs Type Indicator)
Recommendation
Webtoon

Access to Document

10.1007/978-3-319-29236-6_11

Cite this

Yi, M. Y., Lee, O. J., & Jung, J. J. (2016). MBTI-based collaborative recommendation system: A case study of Webtoon contents. In P. C. Vinh, & V. Alagar (Eds.), Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers (pp. 101-110). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 165). Springer Verlag. https://doi.org/10.1007/978-3-319-29236-6_11

Yi, Myeong Yeon ; Lee, O. Joun ; Jung, Jason J. / MBTI-based collaborative recommendation system : A case study of Webtoon contents. Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. editor / Phan Cong Vinh ; Vangalur Alagar. Springer Verlag, 2016. pp. 101-110 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

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title = "MBTI-based collaborative recommendation system: A case study of Webtoon contents",

abstract = "A large number of Webtoon contents has caused difficulties on finding relevant Webtoons for users. Thereby, an efficient recommendation services are needed. However, since the existing recommendation method (e.g. collaborative filtering) has two fundamental problems: (i.e., data sparsity and scalability problem), it has difficulties with reflecting users{\textquoteright} personality. In this paper, we propose the MBTI-CF method to solve these problems and to involve users{\textquoteright} personality by building personality-based neighborhood using MBTI. In order to verify the efficiency of the proposed method, we conducted statistical testing by user survey (anonymous users have rated set of the pre-selected Webtoon contents). Three experimental results have shown that MBTI-CF provides improvement in terms of the data sparsity problem and the scalability problem and offers more stable performance.",

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note = "Funding Information: This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP (Institute for Information & communications Technology Promotion). Also, this work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154). Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.; 4th International Conference on Context-Aware Systems and Applications, ICCASA 2015 ; Conference date: 26-11-2015 Through 27-11-2015",

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Yi, MY, Lee, OJ & Jung, JJ 2016, MBTI-based collaborative recommendation system: A case study of Webtoon contents. in PC Vinh & V Alagar (eds), Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 165, Springer Verlag, pp. 101-110, 4th International Conference on Context-Aware Systems and Applications, ICCASA 2015, Vung Tau, Viet Nam, 26/11/15. https://doi.org/10.1007/978-3-319-29236-6_11

MBTI-based collaborative recommendation system: A case study of Webtoon contents. / Yi, Myeong Yeon; Lee, O. Joun; Jung, Jason J.
Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. ed. / Phan Cong Vinh; Vangalur Alagar. Springer Verlag, 2016. p. 101-110 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 165).

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

TY - GEN

T1 - MBTI-based collaborative recommendation system

T2 - 4th International Conference on Context-Aware Systems and Applications, ICCASA 2015

AU - Yi, Myeong Yeon

AU - Lee, O. Joun

AU - Jung, Jason J.

N1 - Funding Information: This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1018) supervised by the IITP (Institute for Information & communications Technology Promotion). Also, this work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2014R1A2A2A05007154). Publisher Copyright: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

PY - 2016

Y1 - 2016

N2 - A large number of Webtoon contents has caused difficulties on finding relevant Webtoons for users. Thereby, an efficient recommendation services are needed. However, since the existing recommendation method (e.g. collaborative filtering) has two fundamental problems: (i.e., data sparsity and scalability problem), it has difficulties with reflecting users’ personality. In this paper, we propose the MBTI-CF method to solve these problems and to involve users’ personality by building personality-based neighborhood using MBTI. In order to verify the efficiency of the proposed method, we conducted statistical testing by user survey (anonymous users have rated set of the pre-selected Webtoon contents). Three experimental results have shown that MBTI-CF provides improvement in terms of the data sparsity problem and the scalability problem and offers more stable performance.

AB - A large number of Webtoon contents has caused difficulties on finding relevant Webtoons for users. Thereby, an efficient recommendation services are needed. However, since the existing recommendation method (e.g. collaborative filtering) has two fundamental problems: (i.e., data sparsity and scalability problem), it has difficulties with reflecting users’ personality. In this paper, we propose the MBTI-CF method to solve these problems and to involve users’ personality by building personality-based neighborhood using MBTI. In order to verify the efficiency of the proposed method, we conducted statistical testing by user survey (anonymous users have rated set of the pre-selected Webtoon contents). Three experimental results have shown that MBTI-CF provides improvement in terms of the data sparsity problem and the scalability problem and offers more stable performance.

KW - Collaborative filtering

KW - MBTI (Myers-Briggs Type Indicator)

KW - Recommendation

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SN - 9783319292359

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 101

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BT - Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers

A2 - Vinh, Phan Cong

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PB - Springer Verlag

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Yi MY, Lee OJ, Jung JJ. MBTI-based collaborative recommendation system: A case study of Webtoon contents. In Vinh PC, Alagar V, editors, Context-Aware Systems and Applications - 4th International Conference, ICCASA 2015, Revised Selected Papers. Springer Verlag. 2016. p. 101-110. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-319-29236-6_11

MBTI-based collaborative recommendation system: A case study of Webtoon contents

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Keywords

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