Automating Knowledge Flows by Extending Conventional Information Retrieval and Workflow Technologies

Persistent Link:
http://hdl.handle.net/10150/194625
Title:
Automating Knowledge Flows by Extending Conventional Information Retrieval and Workflow Technologies
Author:
Sarnikar, Surendra
Issue Date:
2007
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:
The efficiency of knowledge flow has been observed to be an important factor in the success of large corporations and communities. In recent years, the concept of knowledge flow has been widely investigated from economics, organizational science and strategic management perspectives. In this dissertation, we study knowledge flows from an Information Technology perspective. The technological challenges to enabling the efficient flow of knowledge can be characterized by two key problems, the passive nature of current knowledge management technologies and the information overload problem.In order to enable efficient flow of knowledge, there is a need for high precision recommender systems and proactive knowledge management technologies that automate knowledge delivery and enable the regulation, control and management of knowledge flows. Although several information retrieval and filtering techniques have been developed over the past decade, delivering the right knowledge to the knowledge workers within the right context remains a difficult problem.In this dissertation, we integrate and build upon the information retrieval and workflow literature to develop and evaluate technologies that address the critical gap in current knowledge management systems. Specifically, we make the following key contributions: (1) we demonstrate a concept-hierarchy-based filtering mechanism and evaluate its efficiency for knowledge distribution. (2) We propose a new architecture that supports the automation of knowledge flow via task-centric document recommendation, and develop a query generation technique for automatically deriving queries from task descriptions and evaluate its efficacy in a domain-specific corpus. (3) We develop an analytical model for predicting the performance of a query and validate the model by analyzing its performance in several domain-specific corpora. (4) We propose a new type of workflow called knowledge workflows to automate the flow of knowledge in an enterprise and present a formal model for representing and executing knowledge workflows.The lack of an enterprise wide knowledge flow infrastructure is one of the major impediments to knowledge sharing across an organization. We believe the technologies proposed in this dissertation will contribute towards a new generation of knowledge management systems that will enable the efficient flow of knowledge and eliminate the technological barriers to knowledge sharing across an organization.
Type:
text; Electronic Dissertation
Degree Name:
PhD
Degree Level:
doctoral
Degree Program:
Management Information Systems; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Zhao, J. Leon
Committee Chair:
Zhao, J. Leon

Full metadata record

DC FieldValue Language
dc.language.isoENen_US
dc.titleAutomating Knowledge Flows by Extending Conventional Information Retrieval and Workflow Technologiesen_US
dc.creatorSarnikar, Surendraen_US
dc.contributor.authorSarnikar, Surendraen_US
dc.date.issued2007en_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.abstractThe efficiency of knowledge flow has been observed to be an important factor in the success of large corporations and communities. In recent years, the concept of knowledge flow has been widely investigated from economics, organizational science and strategic management perspectives. In this dissertation, we study knowledge flows from an Information Technology perspective. The technological challenges to enabling the efficient flow of knowledge can be characterized by two key problems, the passive nature of current knowledge management technologies and the information overload problem.In order to enable efficient flow of knowledge, there is a need for high precision recommender systems and proactive knowledge management technologies that automate knowledge delivery and enable the regulation, control and management of knowledge flows. Although several information retrieval and filtering techniques have been developed over the past decade, delivering the right knowledge to the knowledge workers within the right context remains a difficult problem.In this dissertation, we integrate and build upon the information retrieval and workflow literature to develop and evaluate technologies that address the critical gap in current knowledge management systems. Specifically, we make the following key contributions: (1) we demonstrate a concept-hierarchy-based filtering mechanism and evaluate its efficiency for knowledge distribution. (2) We propose a new architecture that supports the automation of knowledge flow via task-centric document recommendation, and develop a query generation technique for automatically deriving queries from task descriptions and evaluate its efficacy in a domain-specific corpus. (3) We develop an analytical model for predicting the performance of a query and validate the model by analyzing its performance in several domain-specific corpora. (4) We propose a new type of workflow called knowledge workflows to automate the flow of knowledge in an enterprise and present a formal model for representing and executing knowledge workflows.The lack of an enterprise wide knowledge flow infrastructure is one of the major impediments to knowledge sharing across an organization. We believe the technologies proposed in this dissertation will contribute towards a new generation of knowledge management systems that will enable the efficient flow of knowledge and eliminate the technological barriers to knowledge sharing across an organization.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
thesis.degree.namePhDen_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineManagement Information Systemsen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorZhao, J. Leonen_US
dc.contributor.chairZhao, J. Leonen_US
dc.contributor.committeememberGupta, J. Leonen_US
dc.contributor.committeememberNunamaker, Jay F.en_US
dc.contributor.committeememberTanniru, Mohanen_US
dc.identifier.proquest1994en_US
dc.identifier.oclc659746585en_US
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