Litcius/Paper detail

Building a Chatbot on a Closed Domain using RASA

Khang Nhứt Lâm, Nam Nhat Le, Jugal Kalita

202017 citationsDOIOpen Access PDF

Abstract

In this study, we build a chatbot system in a closed domain with the RASA framework, using several models such as SVM for classifying intents, CRF for extracting entities and LSTM for predicting action. To improve responses from the bot, the kNN algorithm is used to transform false entities extracted into true entities. The knowledge domain of our chatbot is about the College of Information and Communication Technology of Can Tho University, Vietnam. We manually construct a chatbot corpus with 19 intents, 441 sentence patterns of intents, 253 entities and 133 stories. Experiment results show that the bot responds well to relevant questions.

Topics & Concepts

ChatbotConstruct (python library)Computer scienceDomain (mathematical analysis)SentenceOpen domainArtificial intelligenceNatural language processingSupport vector machineQuestion answeringInformation retrievalMathematicsProgramming languageMathematical analysisTopic ModelingAI in Service InteractionsAdvanced Text Analysis Techniques