A comprehensive survey and review of machine learning techniques in document processing : Industry applications and future directions
*Manisha TiwariCorresponding authormanisha.tiwari@nmims.eduDepartment of Computer EngineeringMukesh Patel School of Technology Management & EngineeringNMIMS (Deemed-to-be-University)Mumbai, Maharashtra, IndiaView full profile → , Padmanabhan Aitalpadmanabha.aital@nmims.eduDepartment of Technology & ManagementMukesh Patel School of Technology Management & EngineeringNMIMS (Deemed-to-be-University)Mumbai, Maharashtra, IndiaView full profile → , Padmaja Joshipadmaja@cdac.inCentre for Development of Advanced Computing (CDAC)Mumbai, Maharashtra, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Published Online:
- 08 Jun 2024
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1701
- Pages:
- 1177–1188
Abstract
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References
[1] Kanakaris, Nikos et al. “On the Advancement of Project Management through a Flexible Integration of Machine Learning and Operations Research Tools.” International Conference on Operations Research and Enterprise Systems (2019).
[2] Kam K.H. Ng, Chen et al. “A systematic literature review on intelligent automation: Aligning concepts from theory, practice, and future perspectives,” Advanced Engineering Informatics, Volume 47, 101246, (2021) ISSN 1474-0346.
[3] Bhatnagar, Vaibhav, et al. “Descriptive analysis of COVID-19 patients in the context of India.” Journal of Interdisciplinary Mathematics 24.3 : 489-504 (2021).
[4] Spasic I, Nenadic G. “Clinical Text Data in Machine Learning: Systematic Review.’ JMIR Med Inform Med Inform; 8(3) : e17984 (2020).
[5] Pandey et al. “Hybrid deep neural network with adaptive galactic swarm optimization for text extraction from scene images.” Soft Comput 25, 1563–1580 (2021).
[6] Wenxiong Liao, Bi Zeng et al. “Multi-level graph neural net- work for text sentiment analysis”, Computers and Electrical Engineering, Volume 92, 107096, (2021) ISSN 0045-7906.
[7] Wankhade,Rao et al.“A survey on sentiment analysis methods, applications, and challenges.” Artif Intell Rev 55, 5731–5780 (2022).
[8] Shervin Minaee, Kalchbrenner et al. “Deep Learning–based Text Classification: A Comprehensive Review” ACM Computing Surveys, Volume 54 Issue 3 Article No. : 62 pp 1–40
[9] P. Semberecki and H. Maciejewski, “Deep learning methods for subject text classification of articles”, Federated Conference on Computer Science and Information Systems (FedCSIS) pp. 357–360 (2017) ISSN 2300-5963.
[10] Paech, B.et al. “Answering a Request for Proposal – Challenges and Proposed Solutions.” In: Regnell, B., Damian, D. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2012. Lecture Notes in Computer Science, vol 7195. Springer, Berlin, Heidelberg (2012).
[11] Fahad ul Hassan and Tuyen Le, “ Automated Requirements Identification from Construction Contract Documents Using Natural Language Processing”, Journal of Legal Affairs and Dispute Resolution in Engineering and Construction. Journal of Legal Affairs and Dispute Resolution in Engineering and Construction.Volume 12, Issue 2
[12] G. Fantoni, E. Coli et al.“ Text mining tool for translating terms of the contract into technical specifications: Development and application in the railway sector”, Computers in Industry. Volume 124, 103357, ISSN 0166-3615 (2021).
[13] Beason, Sterling; Hinton et al.“Automated Analysis of RFPs using Natural Language Processing (NLP) for the Technology Domain,” SMU Data Science Review Vol. 5 (2021)
[14] Asha Rajbhoj, Padmalata Nistala, Vinay Kulkarni, Pulkit Batra, “AI enabled Project Initiation: An approach based on RFP Response Document ”, ISEC : 15th Innovations in Software Engineering, Article No.: 22 (2022).
[15] Fahad ul Hassan; Tuyen Le et al. “Multi-Class Categorization of Design-Build Contract Requirements Using Text Mining and Natural Language Processing Techniques”, Construction Research Congress (2020).
[16] H. R. Motahari-Nezhad et al. “RFPCog : Linguistic-Based Identification and Mapping of Service Requirements in Request for Proposals (RFPs) to IT Service Solutions, ,” 2016 49th Hawaii International Conference on System Sciences (HICSS), Koloa, HI, USA (2016),
[17] Fahad ul Hassan, Tuyen Le, “Computer-assisted separation of design-build contract requirements to support subcontract drafting,” Automation in Construction. Volume 122, 103479, ISSN 0926-5805 (2021).
[18] A. Sainani, Anish et al.”Extracting and Classifying Requirements from Software Engineering Contracts,” 2020 IEEE 28th International Requirements Engineering Conference (RE), Zurich, Switzerland, pp. 147-157 (2020).
[19] S. Maji, Appe et al. “An Interpretable Deep Learning System for Automatically Scoring Request for Proposals,” 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Washington, DC, USA, pp. 851-855 (2021).
[20] Costal, D., Franch, et al. “ On the Use of Requirement Patterns to Analyse Request for Proposal Documents.” In: Laender, A., Pernici, B., Lim, EP., de Oliveira, J. (eds) Conceptual Modeling. ER 2019. Lecture Notes in Computer Science(), vol 11788. Springer, Cham
[21] Altameem, Ayman, et al. “ P-ROCK: a sustainable clustering algorithm for large categorical datasets.” Intell. Autom. Soft Comput 35.1 : 553-566 (2023).
[22] Ningwei Liu, Charles Feng et al. “Automate RFP Response Generation Process Using FastText Word Embeddings and Soft Cosine Measure,” AICS 2019, Proceedings of the 2019 International Conference on Artificial Intelligence and Computer Science.
[23] Costal, D., Franch et al. “ On the Use of Requirement Patterns to Analyse Request for Proposal Documents.” In: Laender, A., Pernici, B., Lim, EP., de Oliveira, J. (eds) Conceptual Modeling. ER 2019. Lecture Notes in Computer Science(), vol 11788. Springer, Cham.
[24] Pandey, Trilok Nath et al. “ Empirical analysis of machine learning techniques for prediction of indian exchange rate,” Journal of Statistics and Management Systems, 26:1, 13-22.
[25] Bhoyar, Sanjay et al.“ A machine learning-based predictive approach in evaluating consumer behavior,” Journal of Statistics and Management Systems , 26:8 (1955–1963), DOI: 10.47974/JSMS-1131.
[26] Sharma, Ankita & Ghose, Udayan. “ Deep learning based bi-polar sentiment classification of movie reviews in Hindi,” Journal of Statistics and Management Systems, 27:1, 59–86 (2024), DOI: 10.47974/JSMS-1030.
