利用人工智能和机器学习实现物流行业查询自动化的智能系统

Leo Liao, Ang Li
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引用次数: 0

摘要

物流行业的运营商和销售人员经常需要向不同的供应商重复提交相同的询价,并选择为公司带来最大利润的报价[4]。这个过程可能非常费力和繁琐。同时,对于规模较小的公司来说,没有完善的报价信息数据库,监控员工的工作是很难实现的[5]。为了提高这个特定行业的销售工作流程的效率,该应用程序设计了一个平台,可以自动化查询过程,分析来自不同供应商的报价,检索最赚钱的报价,并记录员工所提交的所有查询[6]。经过一系列密集的测试,结果证明是有希望的和令人满意的。在分析了包含行业常用语言的电子邮件列表后,机器学习模型可以成功地获得最具成本效益的价格。员工查询的所有历史记录都可以在任何前端设备上正确显示。总的来说,上述障碍已基本解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Intelligent System to Automate the Inquery in Logistics Industry using AI and Machine Learning
Operator and sales employees in the logistics industry often have to submit the same inquiry repetitively to different vendors and opt in for the quotation that will generate the greatest profit for the company [4]. This process can be very laborious and tedious. Meanwhile, for smaller companies that do not have a well-constructed database for quotation information, monitoring employee’s work is simply difficult to achieve [5]. To increase the efficiency of sales’ workflow in this particular industry, this application devises a platform that automates the inquiry process, analyzes quotations from different vendors, retrieves the most profitable one, and documents all inquiries an employee has committed [6]. The results, after a series of intensive testing, prove to be promising and satisfying. The machine learning model can successfully fetch the most cost-effective price after analyzing a list of emails containing common languages used in the industry. All histories of an employee’s inquiry can be correctly displayed on any front-end device. Overall, the obstacle presented above is largely solved.
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