Master of Science in Computer Science
First Committee Member
Kazem Taghva, Chair
Second Committee Member
Ajoy K. Datta
Third Committee Member
Laxmi P. Gewali
Graduate Faculty Representative
Number of Pages
In this thesis, we report on design and implementation of a Hidden Markov Model (HMM) to extract acronyms and their expansions. We also report on the training of this HMM with Maximum Likelihood Estimation (MLE) algorithm using a set of examples.
Finally, we report on our testing using standard recall and precision. The HMM achieves a recall and precision of 98% and 92% respectively.
Acronyms – Computer programs; Electronic information resource searching; Hidden Markov models; Markov processes
Computer Sciences | Theory and Algorithms
University of Nevada, Las Vegas
Vyas, Lakshmi, "Finding acronyms and their definitions using HMM" (2011). UNLV Theses, Dissertations, Professional Papers, and Capstones. 981.
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