International Journal of Computer Science & Network Security

국제컴퓨터통신보호논문지학회 (International Journal of Computer Science & Network Security)
권호 표지
DOI QR코드

DOI QR Code

A Client-Side App Model for Classifying and Storing Documents

  • 투고 : 2022.05.05
  • 발행 : 2022.05.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

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.

키워드

참고문헌

  1. B. A. Hendal, "Kuwait University faculty's use of electronic resources during the COVID-19 pandemic," Digital Library Perspectives, vol. 36, no. 3, pp. 429-436, 2020. https://doi.org/10.1108/DLP-04-2020-0023
  2. D. Prasad, A. Gadpal, K. Kapadni, M. Visave, K. Sultanpure, M. Visave, and K. Sultanpure, "CascadeTabNet: An approach for an end to end table detection and structure recognition from image-based documents," in 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020.
  3. A. Wahdan, S. A. Hantoobi, S. A. Salloum and K. Shaalan, "A systematic review of text classification research based on deep learning models in Arabic language," International Journal of Electrical and Computer Engineering, vol. 10, no. 6, pp. 6629-6643, 2020. https://doi.org/10.11591/ijece.v10i6.pp6629-6643
  4. M. P. Akhter, Z. Jiangbin, I. R. Naqvi, M. Abdelmajeed, A. Mehmood, and M. T. Sadiq, "Document-Level Text Classification Using Single-Layer Multisize Filters Convolutional Neural Network," IEEE Access, vol. 8, pp. 42689-42707, 2020. https://doi.org/10.1109/access.2020.2976744
  5. M. Kumar, S. Gupta, and N. Mohan, "A computational approach for printed document forensics using SURF and ORB features," Soft Computing, vol. 24, no. 1, p. 13197-13208, 2020. https://doi.org/10.1007/s00500-020-04733-x
  6. I. Lvovich, Y. Lvovich, A. Preobrazhenskiy, Y. Preobrazhenskiy, and O. Choporov, "Optimisation of the Subsystem for the Movement of Electronic Documents in Educational Organization," in 2021 1st International Conference on Technology Enhanced Learning in Higher Education, 2021.
  7. S. Sophonhiranrak, "Features, barriers, and influencing factors of mobile learning in higher education: A systematic review," Heliyon, vol. 7, no. 4, 2021.
  8. S. Gonzalez, A. Valenzuela, and J. Tapia, "Hybrid Two-Stage Architecture for Tampering Detection of Chipless ID Cards," IEEE Transactions on Biometrics Behavior and Identity Science, vol. 3, no. 1, pp. 89-100, 2020.
  9. A. Ayaz and M. Yanartas, "An analysis on the unified theory of acceptance and use of technology theory (UTAUT): Acceptance of electronic document management system (EDMS)," Computers in Human Behavior Reports, vol. 2, 2020. https://doi.org/10.1016/j.chbr.2020.100013
  10. M. B. Divyanshu Singh and V. Yadav, "PDF Classification Using Logistic Regression and Latent Dirichlet Allocation," in Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, 2022.
  11. P. N. Sawadogo, J. Darmont, and C. Nous, "Joint Management and Analysis of Textual Documents and Tabular Data Within the AUDAL Data Lake," in European Conference on Advances in Databases and Information Systems, 2021.
  12. S. Chen, "Research on the Strategy of Electronic Documents Management of Universities Based on Digital Campus," in Proceedings of the 2020 International Conference on Advanced Education, Management and Information Technology, 2020.
  13. S. K. Sreedhar, S. Ahmed, P. M. Flora, L. Hemanth, J. Aishwarya and R. G. Naik, "An Improved Approach of Unstructured Text Document Classification Using Predetermined Text Model and Probability Technique," in Proceedings of the First International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, Chennai, India, 2021.
  14. M. P. Akhter, Z. Jiangbin, I. R. Naqvi, M. Abdelmajeed, A. Mehmood and M. T. Sadiq, "Document-Level Text Classification Using Single-Layer Multisize Filters Convolutional Neural Network," IEEE Access, vol. 8, pp. 42689-42707, 2020. https://doi.org/10.1109/access.2020.2976744
  15. B. Hawash, U. A. Mokhtar, Z. M. Yusof, and M. Mukred, "The adoption of electronic records management system (ERMS) in the Yemeni oil and gas sector: Influencing factors," Records Management Journal, vol. 30, no. 1, pp. 1-22, 2020. https://doi.org/10.1108/rmj-03-2019-0010
  16. A. E. Karrar, "A Proposed Model for Improving the Performance of Knowledge Bases in Real-World Applications by Extracting Semantic Information," International Journal of Advanced Computer Science and Applications, vol. 13, no. 2, pp. 116-123, 2022.
  17. T. Levina, A. Rodionov, and R. Farkhutdinov, "Software module for extracting data from electronic documents," in 2020 International Conference on Electrotechnical Complexes and Systems, 2020.
  18. A. Rosa, I. Pustokhina, E. Lydia, K. Shankar, and M. Huda, "Concept of Electronic Document Management System (EDMS) as an Efficient Tool for Storing Document," Computer Science, 2019.
  19. L. He, B. Agard, and M. Trepanier, "A classification of public transit users with smart card data based on time series distance metrics and a hierarchical clustering method," Transportmetrica A: Transport Science, vol. 16, no. 2, pp. 56-75, 2020. https://doi.org/10.1080/23249935.2018.1479722
  20. P. Gonasagi, R. Pardeshi, and M. Hangarge, "Classification of Documents based on Local Binary Pattern Feature through Age Analysis," in Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, Springer, Singapore, 2020, pp. 265-271.
  21. M. Haque, N. Adnan, M. A. Kabir, M. R. A. Rashid, A. S. M. Yasin, and M. S. Pervez, "An Innovative Approach of Verification Mechanism for Electronic and Printed Documents," International Journal of Advanced Computer Science and Applications, vol. 11, no. 8, pp. 623-627, 2020.
  22. D. P. V. Hoai, H.-T. Duong and V. T. Hoang, "Text recognition for Vietnamese identity card based on deep features network," International Journal on Document Analysis and Recognition, vol. 24, no. 1-2, pp. 123-131, 2021. https://doi.org/10.1007/s10032-021-00363-7
  23. S. Z. F. L. J. H. Changsheng Chen, "Domain Generalization for Document Authentication against Practical Recapturing Attacks," arXiv:2101.01404, 2021.
  24. M. Umair, F. Majeed, M. Shoaib, M. Q. Saleem, M. S. Adrees, A. E. Karrar, S. Khurram, M. Shafiq and J.-G. Choi, "Main Path Analysis to Filter Unbiased Literature," Intelligent Automation and Soft Computing, vol. 32, no. 2, pp. 1179-1194, 2022. https://doi.org/10.32604/iasc.2022.018952