String matching algorithms: to search and compare longest common subsequence strings retrieved from Wagner & Fischer and Hirschberg algorithms on Malay dictionary words / Mohd Razif Mohd Ghazi

Mohd Ghazi, Mohd Razif (1999) String matching algorithms: to search and compare longest common subsequence strings retrieved from Wagner & Fischer and Hirschberg algorithms on Malay dictionary words / Mohd Razif Mohd Ghazi. Degree thesis, Universiti Teknologi MARA (UiTM).

Abstract

Information Technology has enabled information that can be in many forms such as text, image or sound, to be accessed widely using search terms via a computer. Due to this type of popularity and advancement in technology, there is an increased interest in searching Malay text to enable scholars and researchers to access the data on-line. This thesis studies the method of a string searching algorithm. There are two methods being evaluated in this research. These are the Wagner & Fischer and Hirschberg algorithms. These methods were chosen because they are based on dynamic programming. Dynamic programming is used to solve both the String Distance Problem and Longest Common Subsequence (LCS) problem. The results obtained shows searching and comparison of LCS retrieved by both algorithms. Comparing of words is carried out based on Dice coefficient.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Mohd Ghazi, Mohd Razif
97300029
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Abu Bakar, Zainab
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science
Keywords: Malay text, data on-line, dynamic programming
Date: 1999
URI: https://ir.uitm.edu.my/id/eprint/98146
Edit Item
Edit Item

Download

[thumbnail of 98146.pdf] Text
98146.pdf

Download (119kB)

Digital Copy

Digital (fulltext) is available at:

Physical Copy

Physical status and holdings:
Item Status:
Processing

ID Number

98146

Indexing

Statistic

Statistic details