Developing Chatbots for Supporting Health Self-Management

Developing Chatbots for Supporting Health Self-Management

Jesús Fernández-Avelino, Giner Alor-Hernández, Mario Andrés Paredes-Valverde, Laura Nely Sánchez-Morales
DOI: 10.4018/978-1-7998-4730-4.ch006
OnDemand:
(Individual Chapters)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

A chatbot is a software agent that mimics human conversation using artificial intelligence technologies. Chatbots help to accomplish tasks ranging from answering questions, playing music, to managing smart home devices. The adoption of this kind of agent is increasing since people are discovering the benefits of them, such as saving time and money, higher customer satisfaction, customer base growing, among others. However, developing a chatbot is a challenging task that requires addressing several issues such as pattern matching, natural language understanding, and natural language processing, as well as to design a knowledge base that encapsulates the intelligence of the system. This chapter describes the design and implementation of a text/speech chatbot for supporting health self-management. This chatbot is currently based on Spanish. The main goal of this chapter is to clearly describe the main components and phases of the chatbot development process, the methods, and tools used for this purpose, as well as to describe and discuss our findings from the practice side of things.
Chapter Preview
Top

Bots Through Chatbots

At a very basic level, bots are a new user interface. This new user interface lets users interact with services and brands using their favorite messaging apps.

Bots are a new way to expose software services through a conversational interface. Bots are also referred to as chatbots, conversational agents, conversational interfaces, chat agents, and more.

Why do we need these bots? Why would we want to expose a service through a conversation? Why not just build a web page (or a mobile app), like we have been doing for the last 20 years or so? Isn’t that much easier than building bots?

The answer is that things have changed in the software industry and in user behavior, and these changes are making bots more and more compelling to software companies. Here are some key developments (Bouras et al., 2018):

  • 1.

    In the last few years, most users have adopted mobile devices, and it has become harder and more expensive to impress and engage with them through the web. This has made a lot of software providers turn to create native mobile apps (apps that run natively on your phone, for example, Instagram or Google Maps) and exposing these mobile apps through app stores.

  • 2.

    The mobile apps ecosystem quickly became saturated, making it harder and more expensive to compete. In addition, users became tired of installing and uninstalling mobile apps, and only a very few apps prevailed.

  • 3.

    Surprisingly, the apps that prevailed and became very common were the messaging apps. Most modern users have three or more of these apps on their phones.

  • 4.

    The user mind share has stuck with messaging apps. Users spend most of their time in these apps; this is even a growing trend with young users who do not have the “old” notion of the web and spend most of their time in chat. Messaging and the ubiquity of connectivity mean that people are more available and responsive via messaging than the alternative, indirect modes of communication.

  • 5.

    These new apps opened up the ability to expose services, products, and brands on these chat platforms. Slack and Kik launched their platforms in 2015, followed by Facebook, Skype, and Apple in 2016.

  • 6.

    In conjunction with these user and industry trends, technology has made a leap in natural language processing, making it easier (though not easy) to build and construct conversational interfaces.

Complete Chapter List

Search this Book:
Reset