Deep Learning Approach Towards Unstructured Text Data Utilization

Abstract

With the meteoric development of the big data, internet of things (IoT), the very first question is about how to scout the massive volume of data from heterogeneous data sources. The modern tools and techniques commonly used in successful transmuting of well-structured data into business intelligence (BI) clearly don't work when started on unlabeled data. It is needed to have effective and efficient mapping processes to transform unstructured text data to structured text data with assigned categories to make rapid decisions. With the support of modern automatic text mining tools, the decision-making process can now be done efficiently and cost-effectively. The deep learning concept has attained state-of-the-art results. The mapping operation of unstructured text data to classified structured text data will symbolize unstructured data as renewable assets that are well arranged, useful, and meaningful to serve organizational operations. This chapter presented a comparison of conventional and deep learning methods for unstructured text data classification and its challenges.