Publication Date: 2024/02/08
Abstract: Business Organizations are flooded with large pool of unstructured data. Loading these data into business database warranted a lot of processes. Companies having BPO and KPO are working for converting unstructured data into their software database with huge resources through programming, with multiple queries and users. To deal with such complex and perplexed situations need an automated system in place and thereby saving a large amount of time and resources. The aim of the present research was to analyse methodically, the technical works relating to the application of data mining, artificial intelligence (AI) and machine learning (ML) in the software industry. In this paper combining with different disciplines of data mining techniques, ML and NLP. Objective of this paper is to improve the organization's business intelligence process through maximum exploitation of unstructured data owned by them. This paper primarily attempts to examine the applicability of combination of data mining techniques, NLP and ML in handling unstructured data and reduces the burden on users by minimizing the usage of multiple queries and make them user-friendly to extract data from large database.
Keywords: Application Database, Data mining, ML, NLP.
DOI: https://doi.org/10.5281/zenodo.10634318
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24JAN1677.pdf
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