Document distribution in a large corporation requires a set of routing procedures for each type of document. Documents may include memorandums, payroll reports, technical reports, external correspondence, and internal mail. Some of these documents may require managerial review and signature release authority to leave the organization. The document must be routed through the different levels of the organization according to the document procedures. The availability of the signers and reviewers becomes a delay factor in the routing of the document. This dissertation describes an approach to a solution to this problem using artificial intelligence and expert system concepts coupled with distributed computer networking to distribute the documents. A prototype system has been demonstrated. A document is originated as an "electronic file" on a user workstation (WS), called the Writer. The document is processed by an inference engine in the WS which also appends the list of Signers and Reviewers. The document is then sent to a Knowledge Base Server (KBS) which adds additional information regarding the distribution of the document. Each document contains headers for the communications network in the organization, distribution control header, and the document text body. The KBS stores the document according to the user profiles in the organizations. Activity of reviewing and signing the documents is originated at the user WS. The document is retrieved from the KBS, reviewed by the user, signed and returned to the KBS for intermediate storage. When the KBS has determined that the document has all the required signatures (Signwords), the document is sent to the final destination. The automated document distribution system summarized above has been demonstrated using a C language implementation on PC workstations and a UNIX-based KBS. The PCs are AT&T 6300 systems and the KBS is an AT&T 3B2/310 system. The communications network is a Sytek LocalNet 20 broadband local area network. Knowledge about document processing and distribution is distributed between local workstations' knowledge bases and the KBS. The second phase of the project involves implementing the system using AI and expert systems tools in the PCs and KBS.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/184596 |
| Date | January 1988 |
| Creators | Mohamed, Shamboul Adlan. |
| Contributors | Martinez, Ralph, Hill, Frederick J., Schooley, Larry C. |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | text, Dissertation-Reproduction (electronic) |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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