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Daniel Schmidt Master Thesis - Final.pdf (694.71 KB)
ETD Abstract Container
Abstract Header
Identifying Knowledge Gaps Using a Graph-based Knowledge Representation
Author Info
Schmidt, Daniel P.
ORCID® Identifier
http://orcid.org/0000-0002-9603-9529
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=wright1588866076446257
Abstract Details
Year and Degree
2020, Master of Science (MS), Wright State University, Computer Science.
Abstract
Knowledge integration and knowledge bases are becoming more and more prevalent in the systems we use every day. When developing these knowledge bases, it is important to ensure the correctness of the information upon entry, as well as allow queries of all sorts; for this, understanding where the gaps in knowledge can arise is critical. This thesis proposes a descriptive taxonomy of knowledge gaps, along with a framework for automated detection and resolution of some of those gaps. Additionally, the effectiveness of this framework is evaluated in terms of successful responses to queries on a knowledge base constructed from a prepared set of instructions.
Committee
Pascal Hitzler, Ph.D. (Advisor)
Michael Raymer, Ph.D. (Committee Member)
John Gallagher, Ph.D. (Committee Member)
Christopher Myers, Ph.D. (Committee Member)
Pages
79 p.
Subject Headings
Computer Science
Keywords
knowledge gap
;
computer science
;
knowledge integration
;
gap identification
;
gap resolution
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Citations
Schmidt, D. P. (2020).
Identifying Knowledge Gaps Using a Graph-based Knowledge Representation
[Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1588866076446257
APA Style (7th edition)
Schmidt, Daniel.
Identifying Knowledge Gaps Using a Graph-based Knowledge Representation.
2020. Wright State University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=wright1588866076446257.
MLA Style (8th edition)
Schmidt, Daniel. "Identifying Knowledge Gaps Using a Graph-based Knowledge Representation." Master's thesis, Wright State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1588866076446257
Chicago Manual of Style (17th edition)
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Document number:
wright1588866076446257
Download Count:
1,172
Copyright Info
© 2020, some rights reserved.
Identifying Knowledge Gaps Using a Graph-based Knowledge Representation by Daniel P. Schmidt is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Wright State University and OhioLINK.