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Information Retrieval Chatbots Based on Conceptual Models

机译:基于概念模型的信息检索聊天机器人

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Customer support systems based on chatbots gain an increasing popularity. Chatbots are becoming more and more important to a plethora of applications not only for social services. Modern information retrieval (IR) chatbots are based on simple queries to a database and do not ensure intelligent dialogues with users. In this paper we propose an IR-chatbot model that incorporates a concept-based knowledge model and an index-guided traversal through it to ensure the discovery of information relevant for users and coherent to their preferences. The proposed approach not only supports a search session, but also helps users to discover properties of items and sequentially refine an imprecise query.
机译:基于聊天机器人的客户支持系统越来越受欢迎。聊天机器人对于众多应用程序而言越来越重要,而不仅仅是社交服务。现代信息检索(IR)聊天机器人基于对数据库的简单查询,不能确保与用户的智能对话。在本文中,我们提出了一个IR-chatbot模型,该模型结合了基于概念的知识模型和通过它进行的索引引导遍历,以确保发现与用户相关且与他们的偏好相关的信息。所提出的方法不仅支持搜索会话,而且还可以帮助用户发现项目的属性并依次完善不精确的查询。

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