Association Rule Mining and Information Retrieval Using Stemming and Text Mining Techniques

Abstract

Heterogeneous, complex and enormous data mining plays significant role in the today’s big data scenario all over the globe.  The research paper is intended toward the natural language processing, mining of textual data, and pattern discovery through association rule mining. The research is aimed towards mining of digital news of epidemic diseases and generating the hidden patterns from the corpus data.  The present study also aimed towards developing knowledge discovery system for healthcare for prediction of epidemic viral diseases and their related measures which will be helpful for the healthcare experts, doctors, and healthcare organizations as well as for governments also to take the precautionary measures. The study deigned for predictive analytics of epidemic diseases and their patterns using association rule mining. The precautionary measures for the healthcare and highly impacted geographical location of widespread diseases are generated through the proposed system.