Uncoding library chatbots: deploying a new virtual reference tool at the San Jose State University library

IF 1.3 4区管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

Reference Services Review Pub Date : 2022-10-24 DOI:10.1108/rsr-05-2022-0020

Sharesly Rodriguez, C. Mune

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引用次数: 8

Abstract

PurposeThis paper aims to detail how a university library developed an AI chatbot to meet a growing need for virtual reference services. This chatbot was developed using Google's free Dialogflow bot platform and embedded in the library's website. With the onset of COVID-19 and a greater reliance on virtual services, chatbots have become of increasing interest to libraries as a tool to provide enhanced services during non-staffed hours and to perform basic information triage when virtual chat transactions reach an overwhelming number of available staff.Design/methodology/approachUsing in-depth research into current practices and readily available tools, a small non-technical team at a university library designed and piloted an AI chatbot that employs natural language processing and AI training. This article describes the chatbot development and implementation process. Results of chatbot interactions after one academic year of usage are also reviewed.FindingsThis study reveals that a university library chatbot may be developed and deployed with minimal coding knowledge using existing tools. Chatbot content can be populated through current library information sources and trained to address typical information inquiries. However, additional development and testing is needed to increase user engagement.Originality/valueThis study indicates that libraries can develop and deploy chatbots to meet user information inquiries without onerous technical training or IT resources. It describes best practices for chatbots and the steps necessary to deploy a chatbot on a library website.

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解密图书馆聊天机器人:在圣何塞州立大学图书馆部署一个新的虚拟参考工具

本文旨在详细介绍一所大学图书馆如何开发人工智能聊天机器人以满足日益增长的虚拟参考服务需求。这个聊天机器人是使用谷歌的免费对话流机器人平台开发的，并嵌入在图书馆的网站上。随着COVID-19的爆发和对虚拟服务的更大依赖，图书馆对聊天机器人越来越感兴趣，因为聊天机器人可以在没有工作人员的时间提供增强的服务，并在虚拟聊天交易达到大量可用工作人员时进行基本信息分类。通过对当前实践和现成工具的深入研究，一所大学图书馆的一个小型非技术团队设计并试用了一个采用自然语言处理和人工智能训练的人工智能聊天机器人。本文描述了聊天机器人的开发和实现过程。在一个学年的使用后，聊天机器人的交互结果也进行了回顾。这项研究表明，大学图书馆聊天机器人可以使用现有的工具开发和部署最少的编码知识。聊天机器人的内容可以通过当前的图书馆信息源进行填充，并经过训练来处理典型的信息查询。然而，需要额外的开发和测试来提高用户粘性。独创性/价值本研究表明，图书馆可以开发和部署聊天机器人来满足用户的信息查询，而无需繁重的技术培训或IT资源。它描述了聊天机器人的最佳实践，以及在图书馆网站上部署聊天机器人所需的步骤。

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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来源期刊

Reference Services Review INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

3.20

自引率

10.00%

发文量

期刊介绍： Reference Services Review (RSR ) is a quarterly, refereed journal dedicated to the enrichment of reference knowledge and the advancement of reference services. RSR covers all aspects of reference functions, including automation of reference services, evaluation and assessment of reference functions and sources, models for delivering quality reference services in all types and sizes of libraries, development and management of teaching/learning activities, promotion of information literacy programs, and partnerships with other entities to achieve reference goals and objectives. RSR prepares its readers to understand and embrace current and emerging technologies affecting reference functions, instructional services and information needs of library users.