Crawford, Daniel
(2020)
Language family analysis and geocomputation.
Undergraduate Thesis, University of Pittsburgh.
(Unpublished)
Abstract
With the fast-growing pace of advancements in computer science, mathematics, and linguistics, great strides have been made in each field. Here, work regarding the analysis of language families will be presented in an argument for the acceptance of results that are derived from a computational means. Specially, this research leverages machine learning methodologies to gain insight into the relationship between, and classification of, different languages and language families. Further, the higher rate of the availability of data regarding the geospatial aspects of a language spreading allows for the incorporation of this data into an analysis of language spread. This research lays the foundation and establishes a framework in which these two aspects, computational analysis and geospatial data, are intertwined to offer a perspective and glean insight into language.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
4 May 2020 |
| Date Type: |
Publication |
| Defense Date: |
16 April 2020 |
| Approval Date: |
4 May 2020 |
| Submission Date: |
17 April 2020 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
43 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Dietrich School of Arts and Sciences > Mathematics
David C. Frederick Honors College |
| Degree: |
BS - Bachelor of Science |
| Thesis Type: |
Undergraduate Thesis |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
phylogenetic analysis, linguistics, clustering, language family, gradient descent, machine learning, R |
| Date Deposited: |
04 May 2020 15:29 |
| Last Modified: |
04 May 2020 15:42 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/38738 |
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