Model of Personal Discount Sensitivity in Recommender Systems

Recommender systems help users to encounter information or items that are of interest to them. Prior work on recommender systems has focused on eliciting preferences for items and neglected the personal traits in discount sensitivity. In this paper, we propose a recommender system that inco...

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Main Authors: Masahiro Sato, Hidetaka Izumo, Takashi Sonoda
Format: Article
Language:English
Published: ASLERD 2016-03-01
Series:Interaction Design and Architecture(s)
Online Access:https://ixdea.org/28_6/
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author Masahiro Sato
Hidetaka Izumo
Takashi Sonoda
author_facet Masahiro Sato
Hidetaka Izumo
Takashi Sonoda
author_sort Masahiro Sato
collection DOAJ
description Recommender systems help users to encounter information or items that are of interest to them. Prior work on recommender systems has focused on eliciting preferences for items and neglected the personal traits in discount sensitivity. In this paper, we propose a recommender system that incorporates the influence of discounts. The effectiveness of the model is verified using a public retail dataset. The discount-sensitive model increased recommendation accuracy and modeling personal differences in this sensitivity further improved it. In order to specify the characteristics of discount sensitivity, the correlations between discount sensitivity and other traits of users and items are also investigated. The results show that discount sensitivity is positively correlated with item popularity and negatively correlated with persistence in purchase behaviors.
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spelling doaj.art-d4ee678c399345749aecbd73c160b6162023-09-03T10:52:36ZengASLERDInteraction Design and Architecture(s)2283-29982016-03-012811012310.55612/s-5002-028-006Model of Personal Discount Sensitivity in Recommender SystemsMasahiro SatoHidetaka IzumoTakashi Sonoda Recommender systems help users to encounter information or items that are of interest to them. Prior work on recommender systems has focused on eliciting preferences for items and neglected the personal traits in discount sensitivity. In this paper, we propose a recommender system that incorporates the influence of discounts. The effectiveness of the model is verified using a public retail dataset. The discount-sensitive model increased recommendation accuracy and modeling personal differences in this sensitivity further improved it. In order to specify the characteristics of discount sensitivity, the correlations between discount sensitivity and other traits of users and items are also investigated. The results show that discount sensitivity is positively correlated with item popularity and negatively correlated with persistence in purchase behaviors.https://ixdea.org/28_6/
spellingShingle Masahiro Sato
Hidetaka Izumo
Takashi Sonoda
Model of Personal Discount Sensitivity in Recommender Systems
Interaction Design and Architecture(s)
title Model of Personal Discount Sensitivity in Recommender Systems
title_full Model of Personal Discount Sensitivity in Recommender Systems
title_fullStr Model of Personal Discount Sensitivity in Recommender Systems
title_full_unstemmed Model of Personal Discount Sensitivity in Recommender Systems
title_short Model of Personal Discount Sensitivity in Recommender Systems
title_sort model of personal discount sensitivity in recommender systems
url https://ixdea.org/28_6/
work_keys_str_mv AT masahirosato modelofpersonaldiscountsensitivityinrecommendersystems
AT hidetakaizumo modelofpersonaldiscountsensitivityinrecommendersystems
AT takashisonoda modelofpersonaldiscountsensitivityinrecommendersystems