An Ontology-based Approach for Mobile Personalized Recommendation

被引：4

作者：

Xu Yingchen ^{[1
]}

Gu Junzhong ^{[1
]}

Yang Jing ^{[1
]}

Zhang Zhengyong ^{[1
]}

机构：

[1] E China Normal Univ, Comp Sci & Technol Dept, Shanghai 200062, Peoples R China

来源：

2009 IITA INTERNATIONAL CONFERENCE ON SERVICES SCIENCE, MANAGEMENT AND ENGINEERING, PROCEEDINGS | 2009年

关键词：

ontology; location awareness; mobile; recommendation; personalization;

D O I：

10.1109/SSME.2009.111

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Mobile devices are in a widespread use today. Restricted by the features of mobile devices, such as mobility, low communication bandwidth, small capacity of memory, limited power and inconvenient interaction, mobile services are required to recommend items adapting to the user need and location. Much existing research on recommendations ignores semantic information of user dynamic historical preferences which is vital to the quality of recommendation. In this paper, an ontology-based approach for mobile personalized recommendation is proposed. This paper gives weight values to historical preferences using a decay factor and a time window. Then, historical preferences are mapped into the domain ontology and generate the User Dynamic Preference Ontology (UDPO), which is stored in mobile devices to reduce the load of bandwidth. After building UDPO, the user profile, the domain ontology and UDPO are combined to calculate the set of recommended items. Here, the user profile involves the user location and the user interests. The experimental results show that our approach can provide Points of Interest which the user likes better.

引用

页码：336 / 339

页数：4

共 12 条

[1]

[Anonymous], 1997, PROC 10 RES COMPUTAT

[2] Fab: Content-based, collaborative recommendation [J].

Balabanovic, M ;

Shoham, Y .

COMMUNICATIONS OF THE ACM, 1997, 40 (03) :66-72

[3] A framework for developing mobile, context-aware applications [J].

Biegel, G ;

Cahill, V .

SECOND IEEE ANNUAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS, PROCEEDINGS, 2004, :361-365

[4]

BURKE R, 2000, LECT NOTES COMPUTER

[5]

GU T, 2004, VEH TECHN C

[6]

Guarino Nicola., 1995, VERY LARGE KNOWLEDGE, P1

[7]

HOLTKAMP B, 2003, P ECHALLENGES

[8] GroupLens: Applying collaborative filtering to Usenet news [J].

Konstan, JA ;

Miller, BN ;

Maltz, D ;

Herlocker, JL ;

Gordon, LR ;

Riedl, J .

COMMUNICATIONS OF THE ACM, 1997, 40 (03) :77-87

[9]

MENG X, 2008, J SOFTWARE, P545

[10]

Roman M., 2002, IEEE Pervasive Computing, V1, P74, DOI 10.1109/MPRV.2002.1158281

← 1 2 →