Automatic Digital Document Processing And Management

This text reviews the issues involved in handling and processing digital documents. Examining the full range of a document’s lifetime, the book covers acquisition, representation, security, pre-processing, layout analysis, understanding, analysis of single components, information extraction, filing, indexing and retrieval. Features: provides a list of acronyms and a glossary of technical terms; contains appendices covering key concepts in machine learning, and providing a case study on building an intelligent system for digital document and library management; discusses issues of security, and legal aspects of digital documents; examines core issues of document image analysis, and image processing techniques of particular relevance to digitized documents; reviews the resources available for natural language processing, in addition to techniques of linguistic analysis for content handling; investigates methods for extracting and retrieving data/information from a document.

Introduction to Electronic Document Management Systems provides an in-depth overview of the technology of electronic document management using modern electronic image processing. It will prove to be a key source of information for management and technical staff of organizations considering a transformation from traditional micrographics-based document storage and retrieval systems to new electronic document capture systems. It will also be useful for those organizations considering improving productivity through electronic management of large volumes of data records.

The world of document management is evolving rapidly, and organizations are increasingly turning to Intelligent Document Processing (IDP) to streamline their document management processes. This comprehensive guide serves as a valuable resource for individuals and organizations embarking on their IDP journey. It offers a step-by-step approach, practical tips, and best practices to help readers successfully implement IDP and achieve significant improvements in efficiency, accuracy, and cost savings. In today's digital age, the volume and complexity of documents continue to grow exponentially, posing significant challenges for organizations across industries. Traditional manual document management processes are time-consuming, error-prone, and resource-intensive, leading to inefficiencies and missed opportunities. However, the advent of Intelligent Document Processing (IDP) presents a game-changing solution. Intelligent Document Processing combines the power of artificial intelligence, machine learning, and automation technologies to extract and process data from unstructured documents swiftly and accurately. By automating manual tasks, organizations can enhance productivity, improve data accuracy, and optimize their document management workflows. This guide serves as a roadmap for readers looking to harness the potential of IDP and transform their document management practices. The chapters of this guide take readers on a comprehensive journey through the world of IDP. It begins with an introduction to document management and the concept of Intelligent Document Processing. Readers will gain a clear understanding of the benefits and importance of implementing IDP in their organizations. The guide then delves into the key aspects of implementing IDP. It covers topics such as assessing document management needs, identifying document types and formats, analyzing document volume and complexity, and evaluating existing document management processes. These chapters provide practical insights, tips, and strategies to help readers assess their current state and identify areas for improvement. As the journey progresses, the guide dives into creating an IDP strategy, including setting clear goals and objectives, selecting the right IDP solution, and defining key performance indicators (KPIs). It emphasizes the importance of customization and adaptation to align with specific organizational needs and goals. The guide further explores preparing documents for IDP, including standardizing formats and layouts, optimizing image quality and resolution, and implementing document classification and indexing. It provides detailed guidance on leveraging intelligent capture technologies, extracting data from structured and unstructured documents, and validating and verifying extracted data. The chapters also cover crucial aspects such as integrating IDP with existing systems, monitoring and measuring IDP performance, change management, and user adoption. They address data security and compliance requirements, as well as provide real-world case studies and success stories to inspire and educate readers. Throughout the guide, readers will find tips, recommendations, and best practices from industry leaders who have successfully implemented IDP. These insights serve as valuable lessons learned and provide practical guidance for readers as they embark on their IDP journey. In conclusion, this comprehensive guide equips readers with the knowledge and tools needed to implement Intelligent Document Processing successfully. By following the chapters, tips, recommendations, and strategies outlined in this guide, organizations can streamline their document management processes, achieve significant improvements in efficiency and accuracy, and drive tangible business outcomes. The IDP journey begins here, offering endless possibilities for optimizing document management in the digital era.

This book constitutes the thoroughly refereed proceedings of the 12th Italian Research Conference on Digital Libraries, IRCDL 2016, held in Firence, Italy, in February 2016. The 15 papers presented were carefully selected from 23 submissions and cover topics such as formal methods, long-term preservation, metadata creation, management and curation, multimedia, ontology and linked data. The papers deal with numerous multidisciplinary aspects ranging from computer science to humanities in the broader sense, including research areas such as archival and library information sciences; information management systems; semantic technologies; information retrieval; new knowledge environments.

This book constitutes the thoroughly refereed proceedings of the 8th Italian Research Conference on Digital Libraries, held in Bari, Italy, in February 2012. The 22 full papers, included together with 4 panel papers, were selected from extended versions of the presentations given at the conference, following an additional round of reviewing and revision after the event. The topics covered are as follows: legacy documents and cultural heritage; systems interoperability and data integration; formal and methodological foundations of digital libraries; semantic web and linked data for digital libraries; multilingual information access; digital library infrastructures; metadata creation and management; search engines for digital library systems; evaluation and log data; handling audio/visual and non-traditional objects; user interfaces and visualization; digital library quality; policies and copyright issues in digital libraries; scientific data curation, citation and scholarly publication, user behavior and modeling; and preservation and curation.

From the participation of researchers in most important international conferences in the field, it is noted that activities in automatic document processing have been continuously growing. This book is an edited volume in Digital Document Processing where the chapters are written by several internationally renowned researchers in the domain. It will be useful for both students and researchers working on various aspects of document image analysis and recognition problems. It contains chapters on topics that are not covered by any textbook, but are more futuristic like “Going beyond the Myth of Paperlessness”, or interesting application areas like “The Role of Document Image Analysis in Trustworthy Elections” as well as “Word Recognition for Museum Index Cards with SNT-Grid”. Persons developing document analysis software for industry may also find the chapters useful and attractive. The language of the chapters is simple and clear, along with drawings/diagrams wherever necessary. An adequate number of references are given at the end of each chapter. Overall, the book is highly readable and will be an asset to the community. Renowned contributors include George Nagy, Hiromichi Fujisawa, F Kimura, D Lopresti, Chew Lim Tan, S Uchida, Thierry Paquet, Laurent Heutte, V Govindaraju, R Manmatha. Contents:Document Image Analysis Using Markovian Models: Application to Historical Documents (S Nicolas, T Paquet and L Heutte)Information Just-in-Time: Going Beyond the Myth of Paperlessness (H Fujisawa, H Ikeda, N Furukawa, K Konishi and S Nakagami)The Role of Document Image Analysis in Trustworthy Elections (G Nagy and D Lopresti)Information Retrieval from Document Image Databases (S Lu and C L Tan)Indexing and Retrieval of Handwritten Documents (H Cao and V Govindaraju)Comprehensive Check Image Reader (M Shridhar, G F Houle, R Bakker and F Kimura)Statistical Deformation Model for Handwritten Character Recognition (S Uchida)Robust Word Recognition for Museum Index Cards with the SNT-Grid (S M Lucas and A Foullon-Pérez)Historical Handwritten Document Recognition (S L Feng and R Manmatha)Statistical Modeling of Document Appearance (P Sarkar)Reverse-Engineering of PDF Files (R Ingold, J-L Bloechle and M Rigamonti)Recognition of Bangla Handwriting: Current Status and Future Directions (U Bhattacharya, S K Parui and B B Chaudhuri) Readership: Engineers & technologists, statisticians, mathematicians and librarians. Keywords:Document Analysis;Document Indexing;Document Retrieval;Handwriting Recognition;Character Recognition;Word Recognition;OCR

Written by a leading authority, this book examines new options for data storage, increased networking capabilities, powerful desktop computing, sophisticated software, and the role they all play in the implementation of a fully integrated electronic document management system (EDMS).

A guide to the information technologies businesses can use to replace cumbersome paper document storage and retrieval. Technologies covered include electronic imaging, automatic indexing, digital storage, telecommunications, networking, and optical character recognition. Annotation c. by Book News,