论文标题
采取最佳的对话策略选择:智能出站机器人的目标驱动方法
Toward An Optimal Selection of Dialogue Strategies: A Target-Driven Approach for Intelligent Outbound Robots
论文作者
论文摘要
随着经济和社会的增长,企业,尤其是金融科技行业的企业,对诸如收货,营销,反欺诈电话等客户的出站呼吁的需求不断增加。但是,大部分重复性和机械工作都占据了人类代理商的大部分时间,因此企业的设备和劳动力成本正在增加。同时,随着过去几十年来人工智能技术的发展,公司使用大数据和人工智能等新技术来增强出口呼叫企业的能力已变得非常普遍。智能出站机器人是人工智能技术在出站呼叫业务领域的典型应用。它主要用于与客户沟通以实现某个目标。它具有低成本,高额重用和易于合规性的特征,这引起了行业的更多关注。 目前,该行业有两种智能出站机器人,但他们俩仍然为改进留下了巨大的空间。其中一种是基于有限状态机,该机器依靠跳跃条件的配置和基于手动体验的相应节点的配置。这种智能出站机器人也称为基于流的机器人。例如,图\ ref {fig {fig:label}显示了基于流的机器人的工作模型的示意图。在每个回合中,机器人都会用与每个节点相对应的单词回复用户。
With the growth of the economy and society, enterprises, especially in the FinTech industry, have increasing demands of outbound calls for customers such as debt collection, marketing, anti-fraud calls, and so on. But a large amount of repetitive and mechanical work occupies most of the time of human agents, so the cost of equipment and labor for enterprises is increasing accordingly. At the same time, with the development of artificial intelligence technology in the past few decades, it has become quite common for companies to use new technologies such as Big Data and artificial intelligence to empower outbound call businesses. The intelligent outbound robot is a typical application of the artificial intelligence technology in the field of outbound call businesses. It is mainly used to communicate with customers in order to accomplish a certain target. It has the characteristics of low cost, high reuse, and easy compliance, which has attracted more attention from the industry. At present, there are two kinds of intelligent outbound robots in the industry but both of them still leave large room for improvement. One kind of them is based on a finite state machine relying on the configuration of jump conditions and corresponding nodes based on manual experience. This kind of intelligent outbound robot is also called a flow-based robot. For example, the schematic diagram of the working model of a flow-based robot for debt collection is shown in Fig.\ref{fig:label}. In each round, the robot will reply to the user with the words corresponding to each node.