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Journal articles on the topic 'Intelligent documents'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Lu, Xiaonan, Saurabh Kataria, William J. Brouwer, James Z. Wang, Prasenjit Mitra, and C. Lee Giles. "Automated analysis of images in documents for intelligent document search." International Journal on Document Analysis and Recognition (IJDAR) 12, no. 2 (2009): 65–81. http://dx.doi.org/10.1007/s10032-009-0081-0.

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Ramesh Pingili. "AI-driven intelligent document processing for healthcare and insurance." International Journal of Science and Research Archive 14, no. 1 (2025): 1063–77. https://doi.org/10.30574/ijsra.2025.14.1.0194.

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Healthcare and insurance industries handle millions of documents daily, leading to administrative bottlenecks, errors, and inefficiencies. This paper explores AI-driven Intelligent Document Processing (IDP) for automating claims, medical records, and regulatory compliance documents. Integrating machine learning (ML), natural language processing (NLP), and RPA, IDP reduces document processing time by 80% and error rates by 90%. Case studies from top hospitals and insurers demonstrate AI’s role in streamlining workflows, enhancing patient care, and accelerating claims processing [1]. This resear

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Sambetbayeva, Madina, Inkarzhan Kuspanova, Aigerim Yerimbetova, Sandugash Serikbayeva, and Shynar Bauyrzhanova. "Development of intelligent electronic document management system model based on machine learning methods." Eastern-European Journal of Enterprise Technologies 1, no. 2(115) (2022): 68–76. http://dx.doi.org/10.15587/1729-4061.2022.251689.

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With the daily increase in document flow, as well as the transition to paperless document management around the world, the demand for electronic document management systems is increasing. This significantly requires optimization of these systems in terms of quality document information retrieval and document management. However, research based on statistical methods cannot effectively handle large amounts of data extracted from electronic documents. In this regard, machine learning methods can effectively solve this problem. This paper presents an approach to building a model of an intelligent

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Madina, Sambetbayeva, Kuspanova Inkarzhan, Yerimbetova Aigerim, Serikbayeva Sandugash, and Bauyrzhanova Shynar. "Development of intelligent electronic document management system model based on machine learning methods." Eastern-European Journal of Enterprise Technologies 1, no. 2(115) (2022): 68–76. https://doi.org/10.15587/1729-4061.2022.251689.

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With the daily increase in document flow, as well as the transition to paperless document management around the world, the demand for electronic document management systems is increasing. This significantly requires optimization of these systems in terms of quality document information retrieval and document management. However, research based on statistical methods cannot effectively handle large amounts of data extracted from electronic documents. In this regard, machine learning methods can effectively solve this problem. This paper presents an approach to building a model of an intelligent

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Movva, Himadeep. "Document Understanding Framework-An Innovative Way to Extract Information from Documents." Journal of Software Engineering and Simulation 9, no. 10 (2023): 34–40. https://doi.org/10.35629/3795-09103440.

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The automation process usually needs input in the form of documents. The information would be extracted from structured, semi-structured, or unstructured documents and ready for a bot to pick up as input data. Using UiPath, we can easily configure rules, including regular expressions, to extract data from digital documents. However, the challenge becomes imminent if the document contains semi-structured, unstructured, or handwritten data. UiPath, with its default features, couldn’t extract reliably content in these cases. UiPath’s document understanding framework is used to extract data from t

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Guo, Zhong Wei, Peng Jiang, Jian Li Zhang, Xiao Song Zhang, and Li Jian Ji. "The Construction of Military Documents Electronic Lexicon." Applied Mechanics and Materials 373-375 (August 2013): 1682–85. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1682.

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Based on the classification system of modern Chinese words classification system and characteristics of military documents field, the military document words are classified and descripted with morphology, syntax, complex feature, semantic and reference. And a military documents electronic lexicon prototype is designed. This lexicon can meet the requirement of military document intelligent processing well proved by application of military documents electronic lexicon.

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Chiang, Tzu-An, Chun-Yi Wu, Charles Trappey, and Amy J. C. Trappey. "An Intelligent System for Automated Binary Knowledge Document Classification and Content Analysis." JUCS - Journal of Universal Computer Science 17, no. (14) (2011): 1991–2008. https://doi.org/10.3217/jucs-017-14-1991.

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Many companies rely on patent engineers to search patent documents and offer recommendations and advice to R and D engineers. Given the increasing number of patent documents filed each year, new means to effectively and efficiently identify and manage technology specific patent documents are required. This research applies a back-propagation artificial neural network (BPANN), a hierarchical ontology technique, and a normalized term frequency (NTF) method to develop an intelligent system for binary knowledge document classification and content analysis. The intelligent system minimizes inapprop

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Palchunov, D. E., and S. I. Chernyavtseva. "Development of Intelligent Assistant for Automated Generation of Department Documents." Programmnaya Ingeneria 14, no. 8 (2023): 388–400. http://dx.doi.org/10.17587/prin.14.388-400.

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The article is devoted to the development of formal mathematical methods for modeling business processes and the application of these methods to create intelligent assistants. The theory of partial models is used to formalize the workflow at the university department. The problem of creating an intelligent assistant for automated generation of university department documents is considered. To solve this problem, an ontological model of the subject area is developed and document templates are built. The focus is on the problem of automated generation of assuredly correct documents. The generati

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Nagasubramanian, Dhivya. "Intelligent Data Extraction from Image Documents." International Journal of Computer Science and Engineering 11, no. 11 (2024): 25–34. https://doi.org/10.14445/23488387/ijcse-v11i11p104.

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Khadim, Umair, Muhammad Munwar Iqbal, and Muhammad Awais Azam. "An Intelligent Three-Level Digital Watermarking Method for Document Protection." April 2021 40, no. 2 (2021): 323–34. http://dx.doi.org/10.22581/muet1982.2102.07.

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Digital text is the most frequent interchange form of data that could hold sensitive information such as audit firms, banks, and educational institutes. This sensitive information needs to preserve its integrity and originality so that it could not only secure the data but also helps to identify ownership of text documents. This paper presents a novel and invisible digital watermarking approach for the secure exchange of text documents over the internet. Digital watermarking serves from the last decade for detection of forgery and tempering from digital text documents and maintained the copyri

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Di Marzo Serugendo, Giovanna, Maria Assunta Cappelli, Gilles Falquet, et al. "Streamlining Tax and Administrative Document Management with AI-Powered Intelligent Document Management System." Information 15, no. 8 (2024): 461. http://dx.doi.org/10.3390/info15080461.

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Organisations heavily dependent on paper documents still spend a significant amount of time managing a large volume of documents. An intelligent document management system (DMS) is presented to automate the processing of tax and administrative documents. The proposed system fills a gap in the landscape of practical tools in the field of DMS and advances the state of the art. This system represents a complex process of integrated AI-powered technologies that creates an ontology, extracts information from documents, defines profiles, maps the extracted data in RDF format, and applies inference t

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Bliźniuk, Grzegorz, Dorota Biernacka, Grażyna Kowalska, and Mariusz Momotko. "EWD-P as an example of a "The Best of Good Practice" project." Journal of Telecommunications and Information Technology, no. 2 (June 30, 2006): 15–23. http://dx.doi.org/10.26636/jtit.2006.2.374.

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The European Document Exchange System – Poland (EWD-P), developed by Rodan Systems SA is one of the most modern electronic document exchange systems in European Union. EWD-P is a workflow system that facilitates decision-making within the state bureaucratic system, with a special brief to work out official Polish government standpoints on numerous legislative issues constantly arising within the EU. The EWD-P project has created an effective platform for electronic exchange of documents related to the EU legislative process. The intelligent workflow management functionality aims to support a c

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Ganapathy, Apoorva, and Takudzwa Fadziso. "Intelligent Indexing and Sorting Management System – Automated Search Indexing and Sorting of Various Topics." Engineering International 8, no. 2 (2020): 101–10. http://dx.doi.org/10.18034/ei.v8i2.554.

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An issue that the majority of the databases face is the static and manual character of indexing activities. This traditional method of indexing and sorting different topics is confirmed to shake the dataset performance somewhat, making downtime and a potential effect in the presentation that is normally addressed by manually indexing operations. Numerous data mining methods can accelerate this process by using proper indexing structures. Choosing the appropriate index generally relies upon the kind of operation that the algorithm performs against the dataset. Topic indexing is the operation of

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Mangave, Shravani Rahul, Samrudhi Sanjaykumar Khade, Rasika Ajit Otari, Pranali Prakash Patil, and Snehal Rayanade. "Brainwave: Empower your knowledge." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 1624–29. https://doi.org/10.22214/ijraset.2025.67540.

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Abstract: Brainwave is a Python-based web application developed to streamline document and project management through intelligent, AI-driven tools. It provides users with features such as interactive chat with PDFs and websites, project-based notetaking, and document summarization using the MapReduce technique. The frontend is built with Streamlit for rapid development, and MongoDB is utilized for efficient data storage. Brainwave integrates advanced Natural Language Processing (NLP) models to offer real-time interaction with documents, making it an essential tool for students and professional

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Guo, Zhong Wei, Qi Long Fu, Bo Yang, Tao Feng, and Meng Zi Zhang. "A Method of Words Classification and Attribute Description for Military Documents Electronic Lexicon." Applied Mechanics and Materials 278-280 (January 2013): 1989–93. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.1989.

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Based on modern Chinese words classification and characteristics of military documents field,the method of classification and attribute description for military document words is presented. Through the description of morphology, syntax, semantic and reference, etc. it realizes the organic combination of words classification and attribute description. This method can meet the requirement of military documents intelligent processing, proved by building the military document electronic lexicon.

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16

Chawla, Suruchi. "Application of Fuzzy C-Means Clustering and Semantic Ontology in Web Query Session Mining for Intelligent Information Retrieval." International Journal of Fuzzy System Applications 10, no. 1 (2021): 1–19. http://dx.doi.org/10.4018/ijfsa.2021010101.

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Information retrieval based on keywords search retrieves irrelevant documents because of vocabulary gap between document content and search queries. The keyword vector representation of web documents is very high dimensional, and keyword terms are unable to capture the semantic of document content. Ontology has been built in various domains for representing the semantics of documents based on concepts relevant to document subject. The web documents often contain multiple topics; therefore, fuzzy c-means document clustering has been used for discovering clusters with overlapping boundaries. In

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17

WANG, JASON T. L., and PETER A. NG. "TEXPROS: AN INTELLIGENT DOCUMENT PROCESSING SYSTEM." International Journal of Software Engineering and Knowledge Engineering 02, no. 02 (1992): 171–96. http://dx.doi.org/10.1142/s0218194092000099.

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This paper presents the design of an intelligent document processing system, called TEXPROS. The system is a combination of filing and retrieval systems, which supports storing, extracting, classifying, categorizing, retrieving and browsing information from a variety of documents. TEXPROS is built based on object-oriented programming and rule-based specification techniques. In this paper, we describe main design goals of the system, its data model, logical file structure, and strategies for document classification and categorization. We also illustrate various retrieval methods and query proce

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Belov, Ilya I. "Automation of Electronic Document Management Systems Functions by Means of Artificial Intelligence Technologies." Herald of an archivist, no. 3 (2022): 772–83. http://dx.doi.org/10.28995/2073-0101-2022-3-772-783.

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The article discusses the use of artificial intelligence technologies in performance of documentation processes in electronic document management systems in order to improve existing practices and to develop methods of using such technologies and implementing some functions automatically without or with minimal human intervention. The scientific novelty of the research is due to an attempt to generalize practical experience of using artificial intelligence technologies to automate electronic document management systems functions by direct development and modernization of such systems and also

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19

DOGUC, Ozge. "AN INTELLIGENT SYSTEM FOR DOCUMENT-BASED BANKING PROCESSES." Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 25, no. 4 (2022): 760–73. http://dx.doi.org/10.17780/ksujes.1166624.

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Business process automation has been helping companies by eliminating mundane and repetitive tasks. Automation tools have been used in many sectors, providing high full-time employee (FTE) savings and low error rates to the companies. Banks have been utilizing the automation tools for core banking and branch operations. In addition, banks receive hundreds of notice documents from courts, municipalities and third parties; which usually contain private and time-sensitive information about their customers. Automated document processing requires special solutions such as optical character recognit

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Al-Dabbagh, Mohammed Mumtaz, Naomie Salim, Amjad Rehman, et al. "Intelligent Bar Chart Plagiarism Detection in Documents." Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/612787.

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This paper presents a novel features mining approach from documents that could not be mined via optical character recognition (OCR). By identifying the intimate relationship between the text and graphical components, the proposed technique pulls out the Start, End, and Exact values for each bar. Furthermore, the word 2-gram and Euclidean distance methods are used to accurately detect and determine plagiarism in bar charts.

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Essin, D. J. "Intelligent Processing of Loosely Structured Documents as a Strategy for Organizing Electronic Health Care Records." Methods of Information in Medicine 32, no. 04 (1993): 265–68. http://dx.doi.org/10.1055/s-0038-1634938.

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AbstractLoosely structured documents can capture more relevant information about medical events than is possible using today’s popular databases. In order to realize the full potential of this increased information content, techniques will be required that go beyond the static mapping of stored data into a single, rigid data model. Through intelligent processing, loosely structured documents can become a rich source of detailed data about actual events that can support the wide variety of applications needed to run a health-care organization, document medical care or conduct research. Abstract

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Taneja, Karan, and Ashok K. Goel. "MuDoC: An Interactive Multimodal Document-grounded Conversational AI System." Proceedings of the AAAI Symposium Series 5, no. 1 (2025): 394–98. https://doi.org/10.1609/aaaiss.v5i1.35619.

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Multimodal AI is an important step towards building effective tools to leverage multiple modalities in human-AI communication. Building a multimodal document-grounded AI system to interact with long documents remains a challenge. Our work aims to fill the research gap of directly leveraging grounded visuals from documents alongside textual content in documents for response generation. We present an interactive conversational AI agent 'MuDoC' based on GPT-4o to generate document-grounded responses with interleaved text and figures. MuDoC's intelligent textbook interface promotes trustworthiness

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Kim, Jinhan, Sanghoon Lee, Seung-won Hwang, and Sunghun Kim. "Towards an Intelligent Code Search Engine." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 1358–63. http://dx.doi.org/10.1609/aaai.v24i1.7503.

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Software developers increasingly rely on information from the Web, such as documents or code examples on Application Programming Interfaces (APIs), to facilitate their development processes. However, API documents often do not include enough information for developers to fully understand the API usages, while searching for good code examples requires non-trivial efforts. To address this problem, we propose a novel code search engine, combining the strength of browsing documents and searching for code examples, by returning documents embedded with high-quality code example summaries mined from

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D, Lande, Soboliev A, and Dmytrenko O. "Intelligent technologies in information retrieval systems." Artificial Intelligence 27, jai2022.27(1) (2022): 260–68. http://dx.doi.org/10.15407/jai2022.01.260.

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This paper considers the use of modern intelligent technologies in information retrieval systems. A general scheme for the implementation of Internet search engines is presented. The existing and prospective approaches to the intellectualization of individual components of this scheme are presented. An approach to the creation of a system of intelligent agents for information collection is presented. These agents are combined into teams and exchange the results of their work with each other. They form a reliable basis for the information base of search engines, ensure uninterrupted operation o

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Hu, Yu. "Neural Network Computing Based Text Mining and its Application." Advanced Materials Research 542-543 (June 2012): 1443–46. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1443.

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With the extensive number of documents that firms must process and with the extensive amounts of information available on the Internet, an automated intelligent method is needed to sort through all available documents or sites. It would be beneficial to start with grouping similar documents or sites together based on similarities. Classifying documents and sorting them into categories could be beneficial since in most cases, no one user would be interested in all the different categories of documents at the same time. Classifying a large number of documents would also make it easier to locate

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Zhou, Guo Hong. "Application of Text Mining Based on Neural Network Computing." Applied Mechanics and Materials 278-280 (January 2013): 1972–75. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.1972.

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Today, numbers of documents that firms must process and with the extensive amounts of information available on the Internet, an automated intelligent method is needed to sort through all available documents or sites. It would be beneficial to start with grouping similar documents or sites together based on similarities. Classifying documents and sorting them into categories could be beneficial since in most cases, no one user would be interested in all the different categories of documents at the same time. Classifying a large number of documents would also make it easier to locate a specific

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Karthika, Gopalakrishnan. "Adoption of Intelligent Automation Tools in the Banking Industry: A Case Study on Leveraging Indico for Document Digitization and Data Extraction." European Journal of Advances in Engineering and Technology 8, no. 9 (2021): 64–68. https://doi.org/10.5281/zenodo.11214008.

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This paper investigates the adoption of intelligent automation tools in the banking industry, with a focus on the application of Indico in digitizing critical documents and extracting data elements. Indico, a cutting-edge platform powered by BERT-based models, offers advanced capabilities for document processing and automation. We explore how this tool can be effectively utilized for digitizing signature cards, W8, W9, legal documents, death certificates, and extracting data from diverse sources such as invoice documents, financial documents, rent rolls, and correspondences. Additionally, the

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Wang, Qin, Shou Ning Qu, Tao Du, and Ming Jing Zhang. "The Research and Application in Intelligent Document Retrieval Based on Text Quantification and Subject Mapping." Advanced Materials Research 605-607 (December 2012): 2561–68. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.2561.

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Nowadays, document retrieval was an important way of academic exchange and achieving new knowledge. Choosing corresponding category of database and matching the input key words was the traditional document retrieval method. Using the method, a mass of documents would be got and it was hard for users to find the most relevant document. The paper put forward text quantification method. That was mining the features of each element in some document, which including word concept, weight value for position function, improved weights characteristic value, text distribution function weights value and

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Chandana Kasibatta, Shreyas Suvarna, Nikhil Chakravarthula, Tagore satya narayana, Mohd Ayaz Uddin, and Dr. M. Ramesh. "Doc Assist: Intelligent Document Processing Assistance for Enhanced Accessibility." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 05 (2025): 2210–14. https://doi.org/10.47392/irjaeh.2025.0324.

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This project presents a desktop assistant designed to retrieve information from non-machine-readable documents, such as scanned images and PDFs. Using Tesseract OCR, the system extracts text, and BM25 is employed for effective document ranking based on user-provided keywords. Additionally, word embeddings are integrated to improve semantic search accuracy. The application is built with Tkinter, offering an intuitive, offline experience. The system's architecture is optimized for quick document retrieval, ensuring minimal resource consumption while maintaining relevance. This documentation cove

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V, Pratham. "AI bot that interacts with multiple pdf's." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41277.

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This project involves the development of an intelligent AI bot capable of interacting with and extracting information from multiple PDF documents. Leveraging advanced natural language processing (NLP) techniques, the AI bot can read, comprehend, and respond to user queries based on the content of multiple PDF files. The bot ensures efficient data retrieval, providing concise and accurate answers, summaries, or insights. This tool aims to streamline the process of document management and information extraction, making it an invaluable asset for research, business, and educational purposes. Key

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Zhang, Lijuan, Lijuan Chen, Shiyang Xu, Liangjun Bai, Jie Niu, and Wanjie Wu. "Design of a Structured Parsing Model for Corporate Bidding Documents Based on Bi-LSTM and Conditional Random Field (CRF)." International Journal of Information Technologies and Systems Approach 16, no. 2 (2023): 1–15. http://dx.doi.org/10.4018/ijitsa.320645.

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International projects are often realized through the bidding process, but the existence of information exchange barriers in different countries leads to a complex and tedious bidding process. In this paper, the authors study the complex problem of reading bidding documents, combine the artificial intelligence to analyze them in a structured way, and realize the intelligent analysis of bidding documents. Firstly, through the CRF model, the structured analysis of the tender document is carried out according to the title of the tender document, and the extraction of quoted price, technology and

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Eambunnapong, Kawitsara, Prachyanun Nilsook, and Panita Wannapiroon. "A Systematic Review of the Intelligent Digital Storytelling Process in Disseminating Health Information." International Journal of Online and Biomedical Engineering (iJOE) 19, no. 07 (2023): 200–223. http://dx.doi.org/10.3991/ijoe.v19i07.37431.

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Digital storytelling is a new concept in education that involves creating meaning. It is a tool with great potential, but in Thailand, it is currently not very popular in terms of sharing stories about disease. This review analyzes the components and processes of intelligent digital storytelling to aid the development of an intelligent digital storytelling platform for disseminating health information. Based on the synthesis of relevant documents, the research process involves 9 main steps: 1) identifying the review objectives, 2) reviewing research questions, 3) determining inclusion criteria

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DI SCIASCIO, EUGENIO, FRANCESCO M. DONINI, and MARINA MONGIELLO. "USING COMPUTATION TREE LOGIC FOR INTELLIGENT INFORMATION SEARCH ON THE WEB." International Journal of Computational Intelligence and Applications 02, no. 03 (2002): 245–53. http://dx.doi.org/10.1142/s1469026802000579.

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Web engines crawl hyperlinks to search for new documents; yet when they index discovered documents they basically revert to conventional information retrieval models and concentrate on the indexing of terms in a single document. We propose to overcome such limits with an approach based on temporal logic. By modeling a web site as a finite state transition system we are able to define complex and selective queries over hyperlinks with the aid of Computation Tree Logic operators. We deployed the proposed approach in a prototype system that allows users pose queries in natural language. Queries a

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Dai, Jianhua, and Jingxin Xu. "Knowledge Graph Construction for Intelligent Media Based on Mobile Internet." Wireless Communications and Mobile Computing 2022 (January 11, 2022): 1–14. http://dx.doi.org/10.1155/2022/4867220.

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Mobile Internet-based intelligent media has become a popular academic topic. This study uses the CiteSpace visualisation tool and Scientific Citation Index Expanded database to comb the existing research in the field of intelligent media from a quantitative perspective. A total of 7248 English papers were published on the topic of “intelligent media” from 2012 to 2021, and 145 highly cited papers refined were analysed. Scientific knowledge graphs were analysed from six dimensions: annual publication quantity, country of publication, institution of publication, author, keywords, and cited refer

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Arora, Shraddha, Mrinal Pandey, Mamta Arora, Komal Gupta, Vineet Sharma, and Lakshay Nagpal. "Digitization of Health Insurance Documents for The Cashless Claim Settlement Using Intelligent Document Management System." Procedia Computer Science 235 (2024): 1319–31. http://dx.doi.org/10.1016/j.procs.2024.04.125.

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Abdelmoumni, Ouadie, and Noureddine Chenfour. "ICHC Framework." International Journal of Software Innovation 10, no. 1 (2022): 1–16. http://dx.doi.org/10.4018/ijsi.293272.

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The Goal in this paper is to propose a cultural heritage data model and evolve towards the creation of a framework based on MongoDB that will allow to manage a JSON model representing the cultural heritage of a city ICHC (Intelligent Cultural Heritage of a City). This manuscript per the authors noticed that during the census of cultural heritage, the presence of human resources linked to heritage is not something that is represented in a smart engine of a framework. Which is why the goal is to integrate the human resource and therefore add a relational aspect to the NoSql documents so that the

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Parra-Amaya, Erika Marcela, Saida Ivonne Rojas-González, Iliana Quintero-Percy, Claudia Cristina Gonzále-Béndiksen De Zaldívar, and Nelson Giovanni Agudelo-Cristancho. "Technological development of functionalities with convolutional neural networks for intelligent document management." Informador Técnico 88, no. 1 (2024): 56–76. http://dx.doi.org/10.23850/22565035.6137.

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In the current highly digitized business landscape, efficient document management is crucial for increasing productivity and optimizing organizational processes. This need has been identified in this document, and an enhanced product named Infopoint, an enterprise content management software has been improved to provide intelligent document management through the implementation of advanced automation and artificial intelligence technologies. In document management, numerous processes are still manually executed, leading to errors and delays due to the burden of repetitive tasks. Manual managem

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Cho, Seongkuk, Jihoon Moon, Junhyeok Bae, Jiwon Kang, and Sangwook Lee. "A Framework for Understanding Unstructured Financial Documents Using RPA and Multimodal Approach." Electronics 12, no. 4 (2023): 939. http://dx.doi.org/10.3390/electronics12040939.

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The financial business process worldwide suffers from huge dependencies upon labor and written documents, thus making it tedious and time-consuming. In order to solve this problem, traditional robotic process automation (RPA) has recently been developed into a hyper-automation solution by combining computer vision (CV) and natural language processing (NLP) methods. These solutions are capable of image analysis, such as key information extraction and document classification. However, they could improve on text-rich document images and require much training data for processing multilingual docum

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Mashchenko, Natalia Evgen'evna, and Elena Valentinovna Gaidar. "Artificial intelligence technologies in the formation of the archival environment: problems and prospects." Историческая информатика, no. 1 (January 2025): 162–73. https://doi.org/10.7256/2585-7797.2025.1.73393.

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The authors studied the prospects of using artificial intelligence (AI) technologies to create and develop a digital archival environment, as well as their impact on the optimization and automation of archived data management processes. The main purpose of the work is to analyze modern digital solutions aimed at improving the processes of storing, searching and processing archival documents (including handwritten, damaged, multilingual). The paper explores key technologies used in digital archives, including intelligent scanning, natural language processing (NLP), computer vision, machine lear

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Texier, Bruno. "IDP : le traitement intelligent de documents passe un cap." Archimag N° 376, no. 6 (2024): 33–37. http://dx.doi.org/10.3917/arma.376.0033.

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Kim, Han-joon, and Sang-goo Lee. "An Intelligent Information System for Organizing Online Text Documents." Knowledge and Information Systems 6, no. 2 (2004): 125–49. http://dx.doi.org/10.1007/s10115-003-0103-z.

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Dr. Marco Antonio Marcos Rodríguez, Dr. Carlos Alfredo Cerna Muñoz, Dra. Aracelli Mónica Aguado Lingán, Dr. Jesús Catherine Saldaña Bocanegra, Dr. Pedro Enrique Zata Pupuche, and Dra. María Salomé Gonzales Lizarme. "Advances In Intelligent Systems: From Artificial Intelligence To Machine Learning And Beyond." Journal of Namibian Studies : History Politics Culture 33 (May 20, 2023): 4605–21. http://dx.doi.org/10.59670/jns.v33i.3966.

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A documentary review was carried out on the production and publication of research papers related to the study of the variables INTELLIGENT SYSTEMS, ARTIFICIAL INTELLIGENCE and AUTOMATIC LEARNING. The purpose of the bibliometric analysis proposed in this document was to know the main characteristics of the volume of publications registered in the Scopus database during the period 2017-2022 by Latin American institutions, achieving the identification of 196 publications. The information provided by this platform was organized through graphs and figures categorizing the information by Year of Pu

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Takama, Yasufumi, and Kaoru Hirota. "Topic-based Intelligent Support System for Information Retrieval." Journal of Advanced Computational Intelligence and Intelligent Informatics 4, no. 6 (2000): 457–63. http://dx.doi.org/10.20965/jaciii.2000.p0457.

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We propose a new concept of intelligent support systems for topic-based information retrieval. As information retrieval (IR) on the World Wide Web (WWW) becomes widespread, new types of tools and systems that do not only find specific pages the user wants, but also and helping the user learn about a particular field of interest are increasingly needed. Two systems based on this consideration are introduced in this paper. One is the Fish View system for supporting document-ordering. It focuses on the user’s document-ordering (making diagrams) while reading, and the user’s viewpoint is represent

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Dr. C. Prema, Dr. G. Jemilda, Mrs.K. Emily Esther Rani, Santhanamari Abi M, Isabel S, and , Jemima Hannah P. "Loan Shield AI Intelligent ID Verification for Efficient Loan Waivers." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 05 (2025): 2682–87. https://doi.org/10.47392/irjaeh.2025.0398.

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Identity authentication is a critical component in the processing of government loan waivers. Manual authentication tends to cause errors and forgery, thus delaying the approval of the loans. To address this, a smart system named Loan Shield AI has been created. It utilizes deep learning, OCR, and federated learning to authenticate documents such as Aadhaar and Smart Cards and auto-extract crucial details. A voice assistant is also provided to assist users by assisting them and completing loan forms from the extracted data. The system is containerized in an application for seamless deployment

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Vuong, Pham, Huy Le Hoang, Phu Ngo Thinh, Nguyen Binh, Nguyen Diem, and D. Nguyen Hien. "Enhancing legal research through knowledge-infusedinformation retrieval for Vietnamese labor law." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 4 (2024): 3962–73. https://doi.org/10.11591/ijai.v13.i4.pp3962-3973.

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The role of intelligent information retrieval systems in legal research optimization has become increasingly recognized. There are many methods for exhibiting advancements in the proficient retrieval of legal documents. However, those methods fail to tackle the specific challenges encountered in real-world labor law searches. This research breaks new ground in Vietnamese labor law retrieval by leveraging a comprehensive dataset of 300,000 documents across diverse categories (20 document types and 27 legal fields) to train and evaluate retrieval models specifically designed for Vietnamese labor

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Rahmawati, Hanifah Indah, Zenita Sabitri, Mutiara Nabila Azmi, and Danny Meirawan. "EXPLORING BIBLIOSHINY FOR MAPPING ARTIFICIAL INTELLIGENCE RESEARCH IN EDUCATION." Jurnal PenSil 14, no. 2 (2025): 223–36. https://doi.org/10.21009/jpensil.v14i2.54083.

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This study critically analyzes the development of artificial intelligence (AI) research in education using a bibliometric approach, leveraging data from 191 Scopus-indexed documents during the 2015-2024 period. Employing Biblioshiny software, the study identifies an annual publication growth rate of 44.22% and an average of 11.88 citations per document. The analysis maps five key clusters: AI-based adaptive learning, automated assessment systems, predictive learning analytics, intelligent pedagogical agents, and personalized learning content. Dominant contributions are observed from countries

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Collen, M. F. "The Use of Documents for Computer-Based Patient Records." Methods of Information in Medicine 32, no. 04 (1993): 269. http://dx.doi.org/10.1055/s-0038-1634946.

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Kizhaev, S. O., V. O. Petrenko, N. V. Mazur, V. V. Belitsky, А. V. Mazur, and O. I. Dudnikova. "Intellectual systems in the management of medical technologies and quality of life." Medicni perspektivi (Medical perspectives) 26, no. 1 (2021): 18–29. http://dx.doi.org/10.26641/2307-0404.2021.1.227724.

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The article is devoted to the development and use of intelligent systems in the management of medical technological processes and health-related quality of life (HRQOL). The relevance of the work is due to the need for effective use of intelligent systems in healthcare. The purpose of this work is to study the possibilities and prospects of using information technologies and artificial intelligence systems in clinical medicine to improve the efficiency of providing medical care to the population. Information retrieval method; theoretical analysis of legislative and regulatory documents, litera

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Kizhaev, S.O., V.O. Petrenko, N.V. Mazur, V.V. Belitsky, А.V. Mazur, and O.I. Dudnikova. "Intellectual systems in the management of medical technologies and quality of life." Medicni perspektivi 26, no. 1 (2021): 18–29. https://doi.org/10.26641/2307-0404.2021.1.227724.

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The article is devoted to the development and use of intelligent systems in the management of medical technological processes and health-related quality of life (HRQOL). The relevance of the work is due to the need for effective use of intelligent systems in healthcare. The purpose of this work is to study the possibilities and prospects of using information technologies and artificial intelligence systems in clinical medicine to improve the efficiency of providing medical care to the population. Information retrieval method; theoretical analysis of legislative and regulatory documents, litera

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.Shanmugarathinam G, Dr. "E-Portal for Case Management using Artificial Intelligence." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47899.

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Abstract the legal sector in India continues to grapple with extensive manual processing of complex and unstructured legal documents. The e-Portal for Case Management using Artificial Intelligence (AI) is a proposed system designed to automate legal document analysis, extraction of relevant events, and classification of case files. This paper presents the design, methodology, and implementation of a case management platform leveraging Natural Language Processing (NLP), Machine Learning (ML), and modern web technologies to streamline legal workflows. The system aims to assist lawyers, judges, a

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