Design and Implementation of a Cognitive Cloud Assistant: A Text Classification Model Approach

Abstract

The main objective of this research was to develop a classification model for the design of a cloud cognitive assistant. The classification model should be able to classify the textual description of the cloud architecture into desired multiple classes. For the purpose of implementation of such assistant, the analysis of current state of cognitive assistants and cloud computing was researched. As for the implementation of classifier, the overview of the possible ways how to create such classifier was also added to the research. Based on the analysis, a solution was proposed for the implementation of a model for text classification, and also a proposal for the implementation of an assistant that would use the proposed model. The Keras library was used to create a sequential text classifier. The IBM Watson cloud services were used to deploy the created model into live environment, and the services from the same group were used to develop a proposed cognitive assistant that was in the end connected to the classifier model.

Keywords

• classification
• cloud computing
• ibm watson
• neural networks