Design of User Profile-based Personalized Recommendation Service for Sport Commerce

@article{ART002219094},
author={ 허철무 },
title={Design of User Profile-based Personalized Recommendation Service for Sport Commerce},
journal={한국지식정보기술학회 논문지},
issn={1975-7700},
year={2017},
volume={12},
number={2},
pages={387-394},
doi={10.34163/jkits.2017.12.2.017},
url={http://dx.doi.org/10.34163/jkits.2017.12.2.017}

TY - JOUR
AU - 허철무
TI - Design of User Profile-based Personalized Recommendation Service for Sport Commerce
T2 - 한국지식정보기술학회 논문지
PY - 2017
VL - 12
IS - 2
PB - 한국지식정보기술학회
SP - 387-394
SN - 1975-7700
AB - Nowadays, many business embed recommendation systems in their web sites, in order to study the tastes of their customers, and achieve some business objectives. Personalized Recommender Service is necessary to latent tendency to optimize service for each user’s unique needs and characteristics. This service is to offer user to customize their service, as well as provide information from their past behaviors. These events have many functions what do they want/need to behaviors and preferences with commerce. Especially, most diversity of commerce serve users with product contents by self-adapting computer system. However, many users don't always know what they want and need, and when their behaviors occasionally change preferences. Besides, users don't find out their purchased history that they want to buy with required product on commerce. After all, personalized recommender service aims to provide with associated services of user’s preference or purchase pattern from the unexpected product information of commercial market. Accordingly, we propose strategies for adaptive personalized recommender service in this paper. Finally, we need to design for adaptable recommender service (tag-based ranking) to support sport commerce. In addition, we make use of adaptive service design, detecting service with user’s data modeling.
KW - Personalized recommender service, Commercial market, User behavior and preference, Adaptive service design, Personalized recommender service (PRS)
DO - 10.34163/jkits.2017.12.2.017
UR - http://dx.doi.org/10.34163/jkits.2017.12.2.017
ER -

허철무 (2017). Design of User Profile-based Personalized Recommendation Service for Sport Commerce. 한국지식정보기술학회 논문지, 12( 2), 387- 394.

허철무 . 2017, “Design of User Profile-based Personalized Recommendation Service for Sport Commerce”, 한국지식정보기술학회 논문지, vol. 12, no. 2, pp. 387-394. Available from: doi:10.34163/jkits.2017.12.2.017

허철무 “Design of User Profile-based Personalized Recommendation Service for Sport Commerce” 한국지식정보기술학회 논문지 12.2 pp. 387-394 (2017): 387.

허철무 . Design of User Profile-based Personalized Recommendation Service for Sport Commerce 한국지식정보기술학회 논문지 [Internet]. 2017; 12( 2), : 387-394. Available from: doi:10.34163/jkits.2017.12.2.017

허철무 . “Design of User Profile-based Personalized Recommendation Service for Sport Commerce” 한국지식정보기술학회 논문지 12, no.2 (2017): 387-394. doi: 10.34163/jkits.2017.12.2.017

홈 권호 목록 논문 목록 논문 상세

Design of User Profile-based Personalized Recommendation Service for Sport Commerce

한국지식정보기술학회 논문지

약어 : 한국지식정보기술학회 논문지

2017, vol.12, no.2, pp.387 - 394

DOI : 10.34163/jkits.2017.12.2.017

발행기관 : 한국지식정보기술학회

연구분야 : 학제간연구

허철무¹

¹성결대학교

인용한 논문 수 : 1 서지 간략 보기

초록

Nowadays, many business embed recommendation systems in their web sites, in order to study the tastes of their customers, and achieve some business objectives. Personalized Recommender Service is necessary to latent tendency to optimize service for each user’s unique needs and characteristics. This service is to offer user to customize their service, as well as provide information from their past behaviors. These events have many functions what do they want/need to behaviors and preferences with commerce. Especially, most diversity of commerce serve users with product contents by self-adapting computer system. However, many users don't always know what they want and need, and when their behaviors occasionally change preferences. Besides, users don't find out their purchased history that they want to buy with required product on commerce. After all, personalized recommender service aims to provide with associated services of user’s preference or purchase pattern from the unexpected product information of commercial market. Accordingly, we propose strategies for adaptive personalized recommender service in this paper. Finally, we need to design for adaptable recommender service (tag-based ranking) to support sport commerce. In addition, we make use of adaptive service design, detecting service with user’s data modeling.

키워드

Personalized recommender service, Commercial market, User behavior and preference, Adaptive service design, Personalized recommender service (PRS)

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