Recommending books of revealed and latent interests in e-commerce

Author

Hirooka, Yasuo ; Terano, Takao ; Otsuka, Yukichi

Author_Institution

Graduate Sch. of Syst. Manage., Tsukuba Univ., Ibaraki, Japan

Volume

3

fYear

2000

fDate

2000

Firstpage

1632

Abstract

We describe TwinFinder: a recommender system for an on-line bookstore. For developing TwinFinder, we extend the capability of conventional content-based recommendation by two novel methods: the Order-Matching Method (OMM) and the Cross-Matching Method (CMM). OMM and CMM aim to provide information of customers´ revealed and latent interest, respectively. Thus, TwinFinder is able to discover new chances to sell books by CMM, while by OMM the system recommends books on customers´ revealed interests. We have implemented and validated TwinFinder in the e-business system of a bookstore in Japan

Keywords

Internet; electronic commerce; information resources; retail data processing; Cross-Matching Method; Internet; Order-Matching Method; TwinFinder; content-based recommendation; e-commerce; latent interest; online bookstore; recommender system; revealed interest; Books; Collaborative work; Control systems; Coordinate measuring machines; Databases; Filtering; Frequency; Internet; Recommender systems; Search methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE

Conference_Location

Nagoya

Print_ISBN

0-7803-6456-2

Type

conf

DOI

10.1109/IECON.2000.972519

Filename

972519