Machine learning approach for finding business partners and building reciprocal relationships

被引:61
|
作者
Mori, Junichiro [1 ]
Kajikawa, Yuya [1 ]
Kashima, Hisashi [1 ]
Sakata, Ichiro [1 ]
机构
[1] Univ Tokyo, Bunkyo Ku, Tokyo 1138656, Japan
关键词
Data mining; Support vector machine; Business development; SUPPORT VECTOR MACHINE; DATA-MINING APPROACH; SUPPLIER SELECTION; BANKRUPTCY PREDICTION; MANAGEMENT; STRATEGY; SYSTEM; VIEW;
D O I
10.1016/j.eswa.2012.01.202
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Business development is vital for any firms. However, globalization and the rapid development of technologies have made it difficult to find appropriate business partners such as suppliers and customers, and build reciprocal relationships among them, while it simultaneously offers many opportunities. In this contribution, we propose AI-based approach to find plausible candidates of business partners using firm profiles and transactional relationships among them. We employ machine learning techniques to build a prediction model of customer-supplier relationships. We applied our approach to the large amount of actual business data. The results showed that our approach successfully found potential business partners with F-values of about 84% and reciprocity among them with F-values of about 77%. Using our method, we also developed the Web-based system that helps people in actual businesses to find their new business partners. These contribute to developing one's own business in the complicated, specialized and rapidly changing business environments of recent years. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:10402 / 10407
页数:6
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