Model-Driven Chatbot Development

Pérez-Soler, Sara; Guerra, Esther; Lara, Juan de

doi:10.1007/978-3-030-62522-1_15

Cited by 41 publications

(14 citation statements)

References 14 publications

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“…The majority of chatbot creation tools rely on the notion of intents [38] as the training data, which are a set of typical human user conversational expressions [39]. Therefore, the training data is composed mainly of intents that are mapped to pre-defined responses.…”

Section: B Build Phasementioning

confidence: 99%

A Conversation-Driven Approach for Chatbot Management

et al. 2022

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Managing and evolving a chatbot's content is a laborious process and there is still a lack of standardization. In this context of standardization, the absence of a management process can lead to bad user experiences with a chatbot. This work proposes the Chatbot Management Process, a methodology for content management on chatbot systems. The proposed methodology is based on the experiences acquired with the development of Evatalk, the chatbot for the Brazilian Virtual School of Government. The focus of this methodology is to evolve the chatbot content through the analysis of user interactions, allowing a cyclic and human-supervised process. We divided the proposed methodology into three distinct phases, namely, manage, build, and analyze. Moreover, the proposed methodology presents a clear definition of the roles of the chatbot team. We validate the proposed methodology along with the creation of the Evatalk chatbot, whose amount of interactions was of 22,771 for the 1,698,957 enrolled attendees in the Brazillian Virtual School of Government in 2020. The application of the methodology on Evatalk's chatbot brought positive results: we reduced the chatbot's human hand-off rate from 44.43% to 30.16%, the chatbot's knowledge base examples increased by 160% whilst maintaining a high percentage of confidence in its responses and keeping the user satisfaction collected in conversations stable.

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Section: B Build Phasementioning

confidence: 99%

A Conversation-Driven Approach for Chatbot Management

et al. 2022

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“…This limitation is shared by proposals focusing on chatbot definition languages, such as [6,14,15], which do not include modeling primitives to define the access-control policies even if modeling of access-control policies is a subject with a long tradition in the MDE community [3], with some notable examples like SecureUML [13] which extends UML with an RBAC metamodel that serves as inspiration for our own proposal. To sum up, we believe ours is the first approach to integrate access-control as first-class citizen in a bot definition language.…”

Section: Related Workmentioning

confidence: 99%

Towards Access Control Models for Conversational User Interfaces

Planas

Martínez

Brambilla

et al. 2022

Enterprise, Business-Process and Information Systems Modeling

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Conversational User Interfaces (CUIs), such as chatbots, are becoming a common component of many software systems and they are evolving in many directions (including advanced features, often powered by AI-based components). However, less attention has been paid to their security aspects, such as access-control, which may pose a clear risk. In this paper, we apply Model-Driven techniques to define more secure CUIs. In particular, we propose a framework to integrate an Access-Control protocol into the CUI specification and implementation through a set of policy rules described using a Domain-Specific Language (DSL) integrated with the core CUI language.

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“…With a more research perspective, we have Xatkit [17] (formerly known as Jarvis [16]), a fully modular and extensible platform-independent chatbot modeling language which provides a meta-model and a textual DSL for defining all types of bots (which we have been used as basis for the generalized metamodel in Sect. 3); CONGA (ChatbOt modeliNg lanGuAge) [36] providing a unifying DSL for specifying some types of chatbots that can then be implemented on top of a couple of chatbot platforms (and even migrated from one to the other); and Baudat et al [5] proposing wcs-OCaml, a new multi-tier chat-bot generator library designed for use with the reactive language Reac-tiveML. Some other works focus on voicebots.…”

Section: Related Workmentioning

confidence: 99%

Towards a model-driven approach for multiexperience AI-based user interfaces

et al. 2021

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Software systems start to include other types of interfaces beyond the “traditional” Graphical-User Interfaces (GUIs). In particular, Conversational User Interfaces (CUIs) such as chat and voice are becoming more and more popular. These new types of interfaces embed smart natural language processing components to understand user requests and respond to them. To provide an integrated user experience all the user interfaces in the system should be aware of each other and be able to collaborate. This is what is known as a multiexperience User Interface. Despite their many benefits, multiexperience UIs are challenging to build. So far CUIs are created as standalone components using a platform-dependent set of libraries and technologies. This raises significant integration, evolution and maintenance issues. This paper explores the application of model-driven techniques to the development of software applications embedding a multiexperience User Interface. We will discuss how raising the abstraction level at which these interfaces are defined enables a faster development and a better deployment and integration of each interface with the rest of the software system and the other interfaces with whom it may need to collaborate. In particular, we propose a new Domain Specific Language (DSL) for specifying several types of CUIs and show how this DSL can be part of an integrated modeling environment able to describe the interactions between the modeled CUIs and the other models of the system (including the models of the GUI). We will use the standard Interaction Flow Modeling Language (IFML) as an example “host” language.

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Model-Driven Chatbot Development

Cited by 41 publications

References 14 publications

A Conversation-Driven Approach for Chatbot Management

A Conversation-Driven Approach for Chatbot Management

Towards Access Control Models for Conversational User Interfaces

Towards a model-driven approach for multiexperience AI-based user interfaces

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