T.V. Prabhakar

Abstract: Providing a multi-modal user interface adds value to any application. Allowing users to speak or chat with the system is one such area where software practitioners are putting a lot of effort. This involves building components which can understand the nuances of human conversation. Such components, often called “chatbots, can be built either from scratch, or using a commercial platform. The process of architecting such applications may differ significantly from the “conventional” applications that the software practitioners usually build. In this work, we present a Reference Architecture for building such applications. We apply the Reference Architecture to a sample use-case and provide two Concrete Architectures for the same. The two architectures are designed keeping in mind, two commercial platforms, IBM Watson Assistant and Google DialogFlow, assuming that they were used to build the conversational components.

Abstract: There is a visible eagerness in the business community to integrate chatbots with their websites and mobile apps. They provide a humanised interface to information and can serve as digital assistants that can perform tasks on behalf of an individual. There are many commercial platforms which provide interfaces to build these chatbots. They are used by both professional software developers as well as people from non-IT backgrounds. Based on our experiences with three popular chatbot-building platforms - Google Dialogflow, IBM Watson Assistant and Amazon Lex, we present a list of desirable features that these platforms should exhibit in order to cater to their mixed user base. We also rate the availability and ease of use of these features on the current versions of these platforms.

Abstract: There is a visible eagerness in the business community to integrate chatbots with their websites and mobile apps. They provide a humanised interface to information and can serve as digital assistants that can perform tasks on behalf of an individual. There are many commercial platforms which provide interfaces to build these chatbots. They are used by both professional software developers as well as people from non-IT backgrounds. Based on our experiences with three popular chatbot-building platforms - Google Dialogflow, IBM Watson Assistant and Amazon Lex, we present a list of desirable features that these platforms should exhibit in order to cater to their mixed user base. We also rate the availability and ease of use of these features on the current versions of these platforms.

Abstract: The article analyses tools and applies the base for processes to the areas of artificial intelligence that are Immersed in the daily lives of people, companies, institutions, and the industry, in constant interaction, without the human beings realizing the process. For achieving this, work has been done on the subarea of conversational agents that offers new ways and experiences of communicating with users. Software modules that have been designed to recognize the patterns of human writing generating an appropriate response. This research presents an analysis of the evolving needs of users and the support of emerging technologies concerning automated communication and the implementation of a prototype of a conversational agent or chatbot that uses artificial intelligence and is focused on natural language processing; the prototype can establish a conversation with students naturally.