A carregar...
Publicação
Conversational AI Assistant Using Artificial Neural Networks: Implementation of a contextual chatbot framework in a Point-of-Sale system
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 2.43 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Artificial intelligence is changing the way how businesses are affronting their day-to-day difficulties.
Chatbots are the perfect demonstration of how simple tasks and queries such as customer support or
sales metrics and reporting could be solved without human intervention. This project introduced a
task-oriented chatbot framework for Spanish language in a Point-Of-Sale webpage. We applied Natural
Language Processing (NLP) techniques such as NER and evaluated two supervised learning methods:
(i) an Artificial Neural Network (ANN) and (ii) a Support Vector Machines (SVM) model to create a
contextualized chatbot that classifies the user’s intention in a text conversation, allowing bidirectional
human-to-machine communication. These intents could go from simple chitchatting to detailed
reports, always providing a natural flow in conversation. The results using an augmented and balanced
corpus suggested that ANN model performed statistically better than SVM. Additionally, a real-word
scenario with a small-talk survey made to five users gave positive feedback about the quality of
predictions. Finally, a software architecture using a PaaS computing service and an API framework was
proposed to implement this dialog system in further works.
Descrição
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
Palavras-chave
Natural Language Processing Name Entity Recognition Natural Language Understanding Artificial Neural Network Support Vector Machine Word Embeddings Chatbot Virtual Assistant