Multi-platform Chatbot Modeling and Deployment with the Jarvis Framework

Autor: Jordi Cabot, Laurent Deruelle, Gwendal Daniel, Mustapha Derras
Rok vydání: 2019
Předmět:
Zdroj: Advanced Information Systems Engineering-31st International Conference, CAiSE 2019, Rome, Italy, June 3–7, 2019, Proceedings
Advanced Information Systems Engineering ISBN: 9783030212896
CAiSE
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Advanced Information Systems Engineering
ISSN: 0302-9743
1611-3349
DOI: 10.1007/978-3-030-21290-2_12
Popis: Chatbot applications are increasingly adopted in various domains such as e-commerce or customer services as a direct communication channel between companies and end-users. Multiple frameworks have been developed to ease their definition and deployment. They typically rely on existing cloud infrastructures and artificial intelligence techniques to efficiently process user inputs and extract conversation information. While these frameworks are efficient to design simple chatbot applications, they still require advanced technical knowledge to define complex conversations and interactions. In addition, the deployment of a chatbot application usually requires a deep understanding of the targeted platforms, increasing the development and maintenance costs. In this paper we introduce the Jarvis framework, that tackles these issues by providing a Domain Specific Language (DSL) to define chatbots in a platform-independent way, and a runtime engine that automatically deploys the chatbot application and manages the defined conversation logic. Jarvis is open source and fully available online.
Databáze: OpenAIRE