Intelligent Document Processing (IDP): A Comprehensive Guide to Streamlining Document Management PDF Download
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Author: Rick Spair
Publisher: Rick Spair
ISBN:
Category : Computers
Languages : en
Pages : 149
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Book Description
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.
Author: Rick Spair
Publisher: Rick Spair
ISBN:
Category : Computers
Languages : en
Pages : 149
Get Book Here
Book Description
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.
Author: LIM ZHI JIAN (TP020087)
Publisher:
ISBN:
Category :
Languages : en
Pages : 90
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Book Description
Author: Lahiru Fernando
Publisher: Notion Press
ISBN:
Category : Computers
Languages : en
Pages : 256
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Book Description
Document processing is a topic that has gained much traction for many years due to its complexity and manual effort. Many document management systems got introduced to simplify document management. At the same time, Robotic Process Automation (RPA) evolved at a rapid pace connecting with state-of-the-art technologies such as Machine Learning (ML), Artificial Intelligence (AI), and Natural Language Processing (NLP) to understand the ways humans communicate. The technology used for AI, ML, and NLP enabled the world to build models that can learn by themselves and use their intelligence to understand the content of any given document. Today, Intelligent Document Processing (IDP) and RPA work together to automate most document-related activities, freeing up users to focus on more critical tasks. Intelligent Document Processing: A Guide for Building RPA Solutions is a mini-guide that gives the readers insights on methods to achieve the best out of Intelligent Document Understanding solutions built within RPA workflows. Further, the mini-book provides real-world use cases, technical challenges, best practices, industry trends, links to many external research articles, and detailed discussions focussing on building effective and scalable RPA solutions to process documents intelligently. The book also contains the author's personal experiences on multiple intelligent document automation projects. This mini-book should be seen as an overview of the current state of technology, with practical guidance and solutions. Best used as a reference guide to help you with your “Optical AI” initiatives.
Author: Gerard Salton
Publisher: Englewood Cliffs, N.J : Prentice-Hall
ISBN:
Category : Computers
Languages : en
Pages : 586
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Book Description
USA. Compilation of papers on technical aspects of fully automatic computer-based information retrieval systems, with particular reference to the experimental smart information system operated at harvard and cornell universities - covers theoretical developments (incl. System evaluation), language analysis techniques, the evaluation of document analysis methodology, user feedback procedures, etc. Diagrams, references and statistical tables.
Author: Stefano Ferilli
Publisher: Springer Science & Business Media
ISBN: 085729198X
Category : Computers
Languages : en
Pages : 313
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Book Description
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.
Author: Pat Myers
Publisher: Packt Publishing Ltd
ISBN: 1785284932
Category : Computers
Languages : en
Pages : 164
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Book Description
Automate the processing of scanned and digital documents by improving accuracy using web-based open and modern intelligent document capture software About This Book Learn how to implement the benefits of intelligent document capture using Ephesoft Enterprise 4 Leverage the power of the open platform to run it as a classic intake capture system to make your current portals or applications more intelligent A practical guide providing examples for optimizing document capture for your business Who This Book Is For This book is intended for information technology professionals interested in installing and configuring Ephesoft Enterprise for their organization, but it is a valuable resource for anyone interested in learning about intelligent document capture. What You Will Learn Discover the benefits of using intelligent document capture in your work place Learn to capture, classify, and separate any type of document Extract important information from your documents Transfer the documents and data into your content management system Customize Ephesoft to meet your unique business requirements Understand the integration techniques using the Ephesoft web services API Convert your paper archive to electronic records efficiently Automate business processes that depend on documents in paper, fax, or email attachment format Implement distributed capture for mailroom automation In Detail Every organization, public or private, processes documents in various formats, especially paper and fax formats. Processing documents manually is an expensive and time-consuming endeavor. Ephesoft Enterprise is a modern document capture solution that allows an organization to automate the business process. It uses powerful technology to classify and capture the vital information from the document's content. This helps to minimize the time your company spends on reviewing and processing any physical and electronic documents. This book teaches you about document capture in general and implementation of document capture using Ephesoft. Start by learning about document capture and how Ephesoft revolutionized the industry. Progress to a tour of key features, including operator and administrator interfaces and then learn to configure Ephesoft to process your business's specific document types and extract content from those documents. You will also get to know the advanced customization techniques that make Ephesoft accommodate your unique business needs. Finally, the book concludes by teaching you how to embed the classification and extraction functionality using Ephesoft's web services. By the end, you will learn to optimize the processing of your documents, saving your company time and money. Style and approach This is a step-by-step guide on how to configure and use Ephesoft using an accounts payable use case. The book will start with basic techniques and progress to more advanced features that allow you to leverage the power for a modern powerful capture system.
Author: Bozzano G Luisa
Publisher: Academic Press
ISBN: 0323140629
Category : Computers
Languages : en
Pages : 269
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Book Description
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.
Author: Qianhong Liu
Publisher: Springer Science & Business Media
ISBN: 1461312957
Category : Computers
Languages : en
Pages : 319
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Book Description
Document Processing and Retrieval: TEXPROS focuses on the design and implementation of a personal, customizable office information and document processing system called TEXPROS (a TEXt PROcessing System). TEXPROS is a personal, intelligent office information and document processing system for text-oriented documents. This system supports the storage, classification, categorization, retrieval and reproduction of documents, as well as extracting, browsing, retrieving and synthesizing information from a variety of documents. When using TEXPROS in a multi-user or distributed environment, it requires specific protocols for extracting, storing, transmitting and exchanging information. The authors have used a variety of techniques to implement TEXPROS, such as Object-Oriented Programming, Tcl/Tk, X-Windows, etc. The system can be used for many different purposes in many different applications, such as digital libraries, software documentation and information delivery. Audience: Provides in-depth, state-of-the-art coverage of information processing and retrieval, and documentation for such professionals as database specialists, information systems and software developers, and information providers.
Author: Sonali Sahu
Publisher: Packt Publishing Ltd
ISBN: 1803233532
Category : Computers
Languages : en
Pages : 246
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Book Description
Build real-world artificial intelligence applications across industries with the help of intelligent document processing Key FeaturesTackle common document processing problems to extract value from any type of documentUnlock deeper levels of insights on IDP in a more structured and accelerated way using AWS AI/MLApply your knowledge to solve real document analysis problems in various industry applicationsBook Description With the volume of data growing exponentially in this digital era, it has become paramount for professionals to process this data in an accelerated and cost-effective manner to get value out of it. Data that organizations receive is usually in raw document format, and being able to process these documents is critical to meeting growing business needs. This book is a comprehensive guide to helping you get to grips with AI/ML fundamentals and their application in document processing use cases. You'll begin by understanding the challenges faced in legacy document processing and discover how you can build end-to-end document processing pipelines with AWS AI services. As you advance, you'll get hands-on experience with popular Python libraries to process and extract insights from documents. This book starts with the basics, taking you through real industry use cases for document processing to deliver value-based care in the healthcare industry and accelerate loan application processing in the financial industry. Throughout the chapters, you'll find out how to apply your skillset to solve practical problems. By the end of this AWS book, you'll have mastered the fundamentals of document processing with machine learning through practical implementation. What you will learnUnderstand the requirements and challenges in deriving insights from a documentExplore common stages in the intelligent document processing pipelineDiscover how AWS AI/ML can successfully automate IDP pipelinesFind out how to write clean and elegant Python code by leveraging AIGet to grips with the concepts and functionalities of AWS AI servicesExplore IDP across industries such as insurance, healthcare, finance, and the public sectorDetermine how to apply business rules in IDPBuild, train, and deploy models with serverless architecture for IDPWho this book is for This book is for technical professionals and thought leaders who want to understand and solve business problems by leveraging insights from their documents. If you want to learn about machine learning and artificial intelligence, and work with real-world use cases such as document processing with technology, this book is for you. To make the most of this book, you should have basic knowledge of AI/ML and python programming concepts. This book is also especially useful for developers looking to explore AI/ML with industry use cases.
Author: Alexander Gelbukh
Publisher: Springer
ISBN: 3540457151
Category : Language Arts & Disciplines
Languages : en
Pages : 456
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Book Description
This book constitutes the refereed proceedings of the Third International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2002, held in Mexico City, Mexico in February 2002. The 44 revised papers presented together with four invited papers were carefully reviewed and selected from a total of 67 submissions. The papers are organized in topical sections on semantics, word sense disambiguation, amaphora, syntax and parsing, part of speech tagging, lexicon and corpus, text generation, morphology, speech, spelling, information extraction and information retrieval, summarization, text mining, and text classification and categorization, document processing, and demo descriptions.
