论文标题
部分可观测时空混沌系统的无模型预测
Do We Need Online NLU Tools?
论文作者
论文摘要
意图识别是任何对话AI应用程序的重要算法。它负责将输入消息分类到有意义的类中。在许多机器人开发平台中，我们可以配置NLU管道。当前有几种意图识别服务可作为API获得，或者我们从许多开源替代方案中进行选择。但是，没有比较意图识别服务和开源算法。许多因素使选择正确的方法在实践中具有挑战性。在本文中，我们建议您为应用程序选择最佳意图识别算法。我们提出一个数据集以进行评估。最后，我们将选定的公共NLU服务与所选的开源算法进行比较，以识别意图。
The intent recognition is an essential algorithm of any conversational AI application. It is responsible for the classification of an input message into meaningful classes. In many bot development platforms, we can configure the NLU pipeline. Several intent recognition services are currently available as an API, or we choose from many open-source alternatives. However, there is no comparison of intent recognition services and open-source algorithms. Many factors make the selection of the right approach to the intent recognition challenging in practice. In this paper, we suggest criteria to choose the best intent recognition algorithm for an application. We present a dataset for evaluation. Finally, we compare selected public NLU services with selected open-source algorithms for intent recognition.
