Award Date

5-2011

Degree Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science

First Committee Member

Kazem Taghva, Chair

Second Committee Member

Ajoy K. Datta

Third Committee Member

Laxmi P. Gewali

Graduate Faculty Representative

Venkatesan Muthukumar

Number of Pages

53

Abstract

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.

Keywords

Acronyms – Computer programs; Electronic information resource searching; Hidden Markov models; Markov processes

Disciplines

Computer Sciences | Theory and Algorithms

Language

English


Share

COinS