Towards a Framework for Classifying Chatbots

Daniel Braun, F. Matthes
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引用次数: 16

Abstract

From sophisticated personal voice assistants like Siri or Alexa to simplistic keyword-based search bots, today, the label “chatbot” is used broadly for all kinds of systems that use natural language as input. However, the systems summarized under this term are so diverse, that they often have very little in common with regard to technology, usage, and their theoretical background. In order to make such systems more comparable, we propose a framework that classifies chatbots based on six categories, which allow a meaningful comparison based on features which are relevant for developers, scientists, and users. Ultimately, we hope to support the scientific discourse, as well as the development of chatbots, by providing an instrument to classify and analyze different groups of chatbot systems regarding their requirements, possible evaluation strategies, available toolsets, and other common features.
一个分类聊天机器人的框架
从Siri或Alexa等复杂的个人语音助手,到简单的基于关键字的搜索机器人,如今,“聊天机器人”这个标签被广泛用于各种使用自然语言作为输入的系统。然而,在这个术语下总结的系统是如此多样化,以至于它们在技术、用法和理论背景方面往往很少有共同之处。为了使这些系统更具可比性,我们提出了一个框架,该框架基于六个类别对聊天机器人进行分类,这允许基于与开发人员,科学家和用户相关的功能进行有意义的比较。最终,我们希望通过提供一种工具来分类和分析不同组的聊天机器人系统,包括它们的需求、可能的评估策略、可用的工具集和其他共同特征,从而支持科学论述以及聊天机器人的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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