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A Client-Side App Model for Classifying and Storing Documents

  • Received : 2022.05.05
  • Published : 2022.05.30

Abstract

Due to the large number of documents that are important to people and many of their requests from time to time to perform an essential official procedure, this requires a practical arrangement and organization for them. When necessary, many people struggle with effectively arranging official documents that enable display, which takes a lot of time and effort. Also, no mobile apps specialize in professionally preserving essential electronic records and displaying them when needed. Dataset consisting of 10,841 rows and 13 columns was analyzed using Anaconda, Python, and Mito Data Science new tool obtained from Google Play. The research was conducted using the quantitative descriptive approach. The presented solution is a model specialized in saving essential documents, categorizing according to the user's desire, and displaying them when needed. It is possible to send in an image or a pdf file. Aside from identifying file kinds like PDFs and pictures, the model also looks for and verifies specific file extensions. The file extension and its properties are checked before sharing or saving it by applying the similarity algorithm (Levenshtein). Our method effectively and efficiently facilitated the search process, saving the user time and effort. In conclusion, such an application is not available, which facilitates the process of classifying documents effectively and displaying them quickly and easily for people for printing or sending to some official procedures, and it is considered one of the applications that greatly help in preserving time, effort, and money for people.

Keywords

References

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