聊天机器人搭建平台的热情好客

S. Srivastava, T. Prabhakar
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引用次数: 6

摘要

能够与机器对话的诱惑并不新鲜。自然语言理解领域的最新进展使得构建可以插入到应用程序中的会话组件成为可能,类似于其他组件。这些被称为聊天机器人的组件可以从零开始创建,也可以借助商业平台创建。这些平台使构建和部署聊天机器人变得更加容易,通常不需要编写一行代码。然而,与任何其他软件组件类似,聊天机器人也有质量问题。尽管在该领域做出了重大贡献,但在文献中缺少构建具有期望质量要求的聊天机器人的架构视角。在当前的工作中,我们强调了这些平台提供的特性(以及它们的质量)对应用程序设计过程和整体质量属性的影响。我们提出了一个方法学框架来评估聊天机器人平台为实现应用程序质量所提供的支持。该框架称为款待框架(Hospitality framework),它基于软件架构的知识体系,尤其是架构策略。该框架生成了一个度量,称为Hospitality Index,它具有为整个应用程序做出各种设计决策的实用程序。我们在一个简单的用例上展示我们的框架的使用,以突出评估的阶段。我们通过选择三个流行的聊天机器人平台——Watson Assistant, DialogFlow和Lex来展示这个过程,超过四个质量属性——可修改性,安全性和隐私性,互操作性和可靠性。我们的研究结果表明,不同的平台对这四个质量属性的支持是不同的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hospitality of chatbot building platforms
The temptation to be able to talk to a machine is not new. Recent advancements in the field of Natural Language Understanding has made it possible to build conversational components that can be plugged inside an application, similar to other components. These components, called chatbots, can be created from scratch or with the help of commercially available platforms. These platforms make it easier to build and deploy chatbots, often without writing a single line of code. However, similar to any other software component, chatbots also have quality concerns. Despite significant contributions in the field, an architectural perspective of building chatbots with desired quality requirements is missing in the literature. In the current work, we highlight the impact of features provided by these platforms (along with their quality) on the application design process and overall quality attributes. We propose a methodological framework to evaluate support provided by a chatbot platform towards achieving quality in the application. The framework, called Hospitality Framework, is based on software architectural body of knowledge, especially architectural tactics. The framework produces a metric, called Hospitality Index, which has utilities for making various design decisions for the overall application. We present the use of our framework on a simple use case to highlight the phases of evaluation. We showcase the process by picking three popular chatbot platforms - Watson Assistant, DialogFlow and Lex, over four quality attributes - Modifiability, Security & Privacy, Interoperability and Reliability. Our results show that different platforms provide different support for these four quality attributes.
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