Machine learning approach for finding business partners and building reciprocal relationships
Machine learning approach for finding business partners and building reciprocal relationships
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DOI：
10.1016/j.eswa.2012.01.202
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发表时间：
2012-09
期刊：
影响因子：
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通讯作者：
Junichiro Mori;Y. Kajikawa;H. Kashima;I. Sakata
中科院分区：
文献类型：
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作者：
Junichiro Mori;Y. Kajikawa;H. Kashima;I. Sakata
业务发展对任何公司来说都是至关重要的。然而，全球化和技术的快速发展使人们很难找到合适的商业伙伴，如供应商和客户，并在他们之间建立互惠关系，同时也提供了许多机会。在这篇文章中，我们提出了一种基于人工智能的方法，利用公司概况和他们之间的交易关系来寻找合理的商业伙伴候选人。我们使用机器学习技术来建立客户-供应商关系的预测模型。我们将我们的方法应用于大量的实际业务数据。结果表明，我们的方法成功地找到了潜在的商业伙伴，它们之间的F值约为84%，互惠程度约为77%。使用我们的方法，我们还开发了基于Web的系统，帮助实际业务中的人们找到他们的新业务伙伴。这些都有助于在近年来复杂、专业和快速变化的商业环境中发展自己的业务。
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.