Abstract
Chatbots are one of the most widely used technologies to implement virtual assistance. Presently, chatbot based virtual assistants are being used by many web administrators to mediate access to data and to carry out generic conversations with the users. Such virtual assistants are getting a lot of attention from the business organizations, as it can help in improving customer care support; reduce the costs in customer service centers and can handle multiple clients at a time. Big data analytics is the process of collecting, organizing and analysing large data sets to discover patterns and unknown correlations hidden in the data, such as usage statistics and customer preferences, which can serve as valuable business information. This paper describes the implementation of a chatbot framework with an interface to big data. This implementation would provide mass knowledge analysis capability to chatbots from distributed environments, which can further the spectrum of usage of such intelligent agents.
Highlights
An intelligent virtual assistant is a software agent which employs the possibilities of Artificial Intelligence, in order to perform tasks or services for a user, based on his/her inputs
While the responses which are more permanent in nature can be stored in the AIML, those responses which need some sort of analysis or which are dynamic in nature can be fetched from the big data
The KB engine communicates with the big data knowledge base through hive interface and finds proper response from the big data using modified AIML responses redirected by the chat engine
Summary
An intelligent virtual assistant is a software agent which employs the possibilities of Artificial Intelligence, in order to perform tasks or services for a user, based on his/her inputs. Known as conversional agents, are software frameworks that can respond to natural language inputs and attempts to hold a conversation in a way that imitates a real person. Chatbots communicate with their human partners through various frameworks ranging from a simple text interface to speech recognition features. Big data analytics enables the analysis of a combination of structured, semi-structured and unstructured data Such an analysis helps to understand the information contained in the data in a better way and requires the use of specialised software frameworks like Hadoop, Spark etc
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