Automated document distribution with signature release authority using AI-based workstations and knowledge base servers.

Persistent Link:
http://hdl.handle.net/10150/184596
Title:
Automated document distribution with signature release authority using AI-based workstations and knowledge base servers.
Author:
Mohamed, Shamboul Adlan.
Issue Date:
1988
Publisher:
The University of Arizona.
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.
Abstract:
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.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Commercial correspondence.; Document delivery.; Expert systems (Computer science)
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Electrical and Computer Engineering; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Martinez, Ralph

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleAutomated document distribution with signature release authority using AI-based workstations and knowledge base servers.en_US
dc.creatorMohamed, Shamboul Adlan.en_US
dc.contributor.authorMohamed, Shamboul Adlan.en_US
dc.date.issued1988en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © 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.en_US
dc.description.abstractDocument 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.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectCommercial correspondence.en_US
dc.subjectDocument delivery.en_US
dc.subjectExpert systems (Computer science)en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorMartinez, Ralphen_US
dc.contributor.committeememberHill, Frederick J.en_US
dc.contributor.committeememberSchooley, Larry C.en_US
dc.identifier.proquest8907407en_US
dc.identifier.oclc701902572en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.