An Text Document Retrieval System for University Support Service on a High Performance Distributed Information System

University support service strategy is to place customers at the center, which is a future insight that customers are the primary source for the growth. The rapid growth of text documents and organizing the data efficiently to support students, and other stakeholders of the organizations is a key challenge. We have built a text document search support system on High Performance Distributed Information System which resolves data handling and serve customers. In this paper, we describe the system architecture, data distribution technique and the retrieval system we have built. Text document classification is carried out using the convolutional neural network (CNN) for efficient retrieval and indexing of the data for crawling. The information is distributed and retrieved based on the identification key using an API based micro-service architecture. The system provides the platform to extract knowledge and channel the data to use by the organization and create on-demand service at the support centers.