Knowledge maps for composite e-services: A mining-based system platform coupling with recommendations

被引：25

作者：

Liu, Duen-Ren ^{[1
]}

Ke, Chih-Kun ^{[1
]}

Lee, Jia-Yuan ^{[1
]}

Lee, Chun-Feng ^{[1
]}

机构：

[1] Natl Chiao Tung Univ, Inst Informat Management, Hsinchu 300, Taiwan

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2008年 / 34卷 / 01期

关键词：

composite e-service; knowledge maps; topic maps; data mining; recommendation;

D O I：

10.1016/j.eswa.2006.10.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Providing various c-services on the Internet by enterprises is an important trend in c-business. Composite e-services, which consist of various e-services provided by different e-service providers, are complex processes that require the cooperation among cross-organizational e-service providers. The flexibility and success of e-business depend on effective knowledge support to access related information resources of composite e-services. Thus, providing effective knowledge support for accessing composite e-services is a challenging task. This work proposes a knowledge map platform to provide an effective knowledge support for utilizing composite e-services. A data mining approach is applied to extract knowledge patterns from the usage records of composite e-services. Based on the mining result, topic maps are employed to construct the knowledge map. Meanwhile, the proposed knowledge map is integrated with recommendation capability to generate recommendations for composite e-services via data mining and collaborative filtering techniques. A prototype system is implemented to demonstrate the proposed platform. The proposed knowledge map enhanced with recommendation capability can provide users customized decision support to effectively utilize composite e-services. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：700 / 716

页数：17

共 41 条

[21] Development of a recommender system based on navigational and behavioral patterns of customers in e-commerce sites [J].

Kim, YS ;

Yum, BJ ;

Song, J ;

Kim, SM .

EXPERT SYSTEMS WITH APPLICATIONS, 2005, 28 (02) :381-393

[22] 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

[23] Web personalization expert with combining collaborative filtering and association rule mining technique [J].

Lee, CH ;

Kim, YH ;

Rhee, PK .

EXPERT SYSTEMS WITH APPLICATIONS, 2001, 21 (03) :131-137

[24] Classification-based collaborative filtering using market basket data [J].

Lee, JS ;

Jun, CH ;

Lee, J ;

Kim, S .

EXPERT SYSTEMS WITH APPLICATIONS, 2005, 29 (03) :700-704

[25] A hybrid collaborative filtering method for multiple-interests and multiple-content recommendation in E-Commerce [J].

Li, Y ;

Lu, L ;

Li, XF .

EXPERT SYSTEMS WITH APPLICATIONS, 2005, 28 (01) :67-77

[26]

Lin F.R., 2003, P 36 ANN HAW INT C S

[27] Designing a composite e-service platform with recommendation function [J].

Liu, DR ;

Shen, MX ;

Liao, CT .

COMPUTER STANDARDS & INTERFACES, 2003, 25 (02) :103-117

[28]

MacQueen J., 1967, Proc fifth Berkeley Symp Math Stat Probab, V1, P281

[29]

PAPAZOGLOU MP, 2002, P 3 VLDB TES WORKSH, P54

[30] Dynamic service aggregation in electronic marketplaces [J].

Piccinelli, G ;

Di Vitantonio, G ;

Mokrushin, L .

COMPUTER NETWORKS-THE INTERNATIONAL JOURNAL OF COMPUTER AND TELECOMMUNICATIONS NETWORKING, 2001, 37 (02) :95-109

← 1 2 3 4 5 →