Automatic document classification and extraction system (ADoCES)

Document processing is a critical element of office automation. Document image processing begins from the Optical Character Recognition (OCR) phase with complex processing for document classification and extraction. Document classification is a process that classifies an incoming document into a particular predefined document type. Document extraction is a process that extracts information pertinent to the users from the content of a document and assigns the information as the values of the “logical structure” of the document type. Therefore, after document classification and extraction, a paper document will be represented in its digital form instead of its original image file format, which is called a frame instance. A frame instance is an operable and efficient form that can be processed and manipulated during document filing and retrieval. This dissertation describes a system to support a complete procedure, which begins with the scanning of the paper document into the system and ends with the output of an effective digital form of the original document. This is a general-purpose system with “learning” ability and, therefore, it can be adapted easily to many application domains. In this dissertation, the “logical closeness” segmentation method is proposed. A novel representation of document layout structure - Labeled Directed Weighted Graph (LDWG) and a methodology of transforming document segmentation into LDWG representation are described. To find a match between two LDWGs, string representation matching is applied first instead of doing graph comparison directly, which reduces the time necessary to make the comparison. Applying artificial intelligence, the system is able to learn from experiences and build samples of LDWGs to represent each document type. In addition, the concept of frame templates is used for the document logical structure representation. The concept of Document Type Hierarchy (DTH) is also enhanced to express the hierarchical relation over the logical structures existing among the documents

e-DOCSPROS : exploring TEXPROS into e-business era

Document processing is a critical element of office automation. TEXPROS (TEXt PROcessing System) is a knowledge-based system designed to manage personal documents. However, as the Internet and e-Business changed the way offices operate, there is a need to re-envision document processing, storage, retrieval, and sharing. In the current environment, people must be able to access documents remotely and to share those documents with others. e-DOCPROS (e-DOCument PROcessing System) is a new document processing system that takes advantage of many of TEXPROS\u27s structures but adapts the system to this new environment. The new system is built to serve e-businesses, takes advantage of Internet protocols, and to give remote access and document sharing. e-DOCPROS meets the challenge to provide wider usage, and eventually will improve the efficiency and effectiveness of office automation. It allows end users to access their data through any Web browser with Internet access, even a wireless network, which will evolutionarily change the way we manage information. The application of e-DOCPROS to e-Business is considered. Four types of business models re considered here. The first is the Business-to-Business (B2B) model, which performs business-to-business transactions through an Extranet. The Extranet consists of multiple Intranets connected via the Internet.The second is the Business-to-Consumer (B2Q model, which performs business-to-consumer transactions through the Internet. The third is the Intranet model, which performs transactions within an organization through the organization\u27s network. The fourth is the Consumer-to-Consumer (C2C) model, which performs consumer-to consumer transactions through the Internet. A triple model is proposed in this dissertation to integrate organization type hierarchy and document type hierarchy together into folder organization. e-DOCPROS introduces new features into TEXPROS to support those four business models and to accommodate the system requirements. Extensible Markup Language (XML), an industrial standard protocol for data exchange, is employed to achieve the goal of information exchange between e-DOCPROS and the other systems, and also among the subsystems within e-DOCPROS. Document Object Model (DOM) specification is followed throughout the implementation of e-DOCPROS to achieve portability. Agent-based Application Service Provider (ASP) implementation is employed in e-DOCPROS system to achieve cost-effectiveness and accessibility

Knowledge management for TEXPROS

Most of the document processing systems today have applied Al technologies to support their system intelligent behaviors. For the application of Al technologies in such systems, the core problem is how to represent and manage different kinds of knowledge to support their inference engine components\u27 functionalities. In other words, knowledge management has become a critical issue in the document processing systems. In this dissertation, within the scope of the TEXt PROcessing System (TEXPROS), we identify knowledge of various kinds that are applicable in the system. We investigate several problems of managing this knowledge and then develop a knowledge base for TEXPROS. In developing this knowledge base, we present approaches to representing and managing different kinds of knowledge to support its inference engine components\u27 functionalities. In TEXPROS, a dual-model paradigm is used, which contains the folder organization and the document type hierarchy, to represent and manage documents. We introduce a new System Catalog structure to represent and manage the knowledge for TEXPROS. This knowledge includes the system-level information of the folder organization and the document type hierarchy, and the operational level information of the document base itself. A unified storage approach is employed to store both the operational level information and system level information. Such storage is to house the frame template base and frame instance base. An enhanced two-level thesaurus model is presented in this dissertation. When dealing with special kinds of data in processing documents, a new structure DataDomain is presented, which supports the extended thesaurus functionalities, pattern recognition and data type operations. Based on the dual-model paradigm of TEXPROS, a concept of “Semantic Range” is presented to solve the sense ambiguity problems. In this dissertation, we also present the approaches to implement the general KeyTerm transformation and approximate term matching of TEXPROS. Finally, a new component “Registration Center” at the knowledge management level of TEXPROS is presented. The registration center aims to help users handle knowledge packages for specific working domain and to solve the knowledge porting problem for TEXPROS. This dissertation is concluded with the future research work