PhD Defense by Yuzhi Guo

Event Details
  • Date/Time:
    • Thursday May 7, 2020
      3:00 pm - 5:00 pm
  • Location: REMOTE
  • Phone:
  • URL: BlueJeans Link
  • Email:
  • Fee(s):
    N/A
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Summaries

Summary Sentence: ENHANCING PUBLIC SECTOR ORGANIZATION KNOWLEDGE RETENTION WITH SOCIAL NETWORK ANALYSIS, TEXT MINING AND MACHINE LEARNING

Full Summary: No summary paragraph submitted.

Ph.D. Thesis Defense Announcement

 

ENHANCING PUBLIC SECTOR ORGANIZATION KNOWLEDGE RETENTION WITH

SOCIAL NETWORK ANALYSIS, TEXT MINING AND MACHINE LEARNING

 

by

Yuzhi Guo

 

Advisor(s):

Dr. David Frost (CEE)

 

Committee Members:

Dr. Umit Catalyurek (CSE), Dr. Polo Chau (CSE), Dr. Tuo Zhao (ISyE), Dr. Wei Deng (Google)

 

 

Date & Time: 3pm May 7, 2020

Location: https://bluejeans.com/4043985879

 Complete announcement, with abstract, is attached

    The technical knowledge and expertise possessed by employees are considered amongst an organization’s greatest assets, but are also most vulnerable and can be easily impacted or lost. The loss of experienced employees and important knowledge can put an organization’s competency in great jeopardy. Thus, it is critical to address the challenge of proper knowledge transfer and retention proactively rather than reactively. Public sector organizations have their unique characteristics and are facing emerging HR challenges due to market changes. Most of the current knowledge retention approaches are either outdated and ineffective or developed without considering the features of public sector organizations. A study that overlaps computational and data science techniques with HR data management in light of these features is considered to be a strategic and systematic development that advances existing methods in knowledge retention and overcomes the emerging HR challenges faced by many large public organizations. 

    In the scope of this work, several data tools are studied for their applications to HR databases, with the objectives of enhancing perception on organization-wide attrition risk distribution, identifying critical knowledge at risk of being lost, and choosing the most suitable provider and recipient for a set of knowledge sharing programs. Moreover, an integrated computational system is developed for Georgia DOT. The system uses an existing HR database and provides modular tools to assist HR personnel strategically plan for a range of activities, aiming for increased level of knowledge transfer and lower employee turnover rate, among other benefits. The system is further evaluated by both user experience feedback, as well as a few “use cases” discussed with the end users.

 

 

 

Additional Information

In Campus Calendar
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Graduate Studies

Invited Audience
Faculty/Staff, Public, Undergraduate students
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Other/Miscellaneous
Keywords
Phd Defense
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Apr 27, 2020 - 1:57pm
  • Last Updated: Apr 27, 2020 - 1:57pm