Conversion of Unstructured File to Structured File in Cloud Computing
Keywords:
Unstructured Data, Cloud Computing, Machine Learning, Natural Language Processing, Data StructuringAbstract
Data in the cloud are rapidly accumulating and are typically unstructured, which makes it difficult to address issues related to storage as well as data search and analysis. This research work focuses on how unstructured computer files can be properly converted to structured format for archival and easy retrieval, in the course of which a cloud based platform that employ NLP, ML and Database Optmisation techniques will be developed. The study uses NLP for text segmentation, ML for classification, and efficient query in the structured databases. The proposed method was tested with set of 10, 000 unstructured files and showed the increase of efficiency of data search for 35% and decrease of the processing time for 28% in comparing with traditional algorithm based on the rules. The data obtained also validated the positive and significant relationship between file size and processing time at R² = 0.82 indicating the GetGood solution should indeed be designed to be scalably. Analyzing the results of the check of the hypothesis through the use of ANOVA showed that the methods yielded statistically significant difference in structuring accuracy at p < 0.05. These studies provide evidence that the structuring that is done by AI improves the access to data and the work of the cloud system. Therefore the key decision for industries with large volumes of unstructured data is to implement automated structuring systems.
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