Similarity Measure for Fiber Clustering: A Constant Time Complexity Algorithm

2015 ◽  
Author(s):  
Tran Anh Quan ◽  
Bay Vo
Keyword(s):  
Similarity Measure ◽  
Time Complexity ◽  
Constant Time ◽  
Fiber Clustering ◽  
Complexity Algorithm

scholarly journals Enhanced Levenshtein Edit Distance Method functioning as a String-to-String Similarity Measure

2016 ◽  
Vol 42 (1) ◽  
pp. 48-54
Author(s):  
Abbas Al-Bakry ◽  
Marwa Al-Rikaby
Keyword(s):  
Similarity Measure ◽  
Time Complexity ◽  
Edit Distance ◽  
Original Method ◽  
Distance Method ◽  
String Similarity

Levenshtein is a Minimum Edit Distance method; it is usually used in spell checking applications for generatingcandidates. The method computes the number of the required edit operations to transform one string to another and it canrecognize three types of edit operations: deletion, insertion, and substitution of one letter. Damerau modified the Levenshteinmethod to consider another type of edit operations, the transposition of two adjacent letters, in addition to theconsidered three types. However, the modification suffers from the time complexity which was added to the original quadratictime complexity of the original method. In this paper, we proposed a modification for the original Levenshtein toconsider the same four types using very small number of matching operations which resulted in a shorter execution timeand a similarity measure is also achieved to exploit the resulted distance from any Edit Distance method for finding the amountof similarity between two given strings.

scholarly journals Perbandingan Algoritma Cheapest Insertion Heuristics dan Pemrograman Dinamis untuk Penyelesaian Traveling Salesman Problem

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Anggar Titis Prayitno
Keyword(s):  
Dynamic Programming ◽  
Traveling Salesman Problem ◽  
Calculation Result ◽  
Efficient Algorithm ◽  
Time Complexity ◽  
Traveling Salesman ◽  
Algorithm Efficiency ◽  
Heuristics Algorithm ◽  
Complexity Algorithm

ABSTRACT  Traveling Salesman Problem (TSP) is one of combinatorics optimation problem to find the possible shorthest path that can be obtained if a  salesman visit each city exactly once and return to the starting city. The shorthest path searching can be done by Cheapest Insertion Heuristics algorithm and Dynamic Programming. Each algorithm has different efficiency to find shorthest path. Algorithm efficiency is determined based on time complexity. Algorithm wich has the smallest time complexity is the most efficient algorithm. Based on the calculation result, the time complexity of Cheapest Insertion Heuristics algorithm is and Dynamic Programming is .  Therefore, for  Cheapest Insertion Heuristics Algorithm is more efficient algorithm than Dynamic Programming in TSP solving. Keywords : Traveling Salesman Problem, Cheapest Insertion Heuristics  Algorithm, Dynamic Programming, and Algorithm time complexity.

scholarly journals A logarithmic time complexity algorithm for pattern searching using product–sum property

2011 ◽  
Vol 62 (5) ◽  
pp. 2162-2168 ◽  
Author(s):  
Khalid Mahmood Aamir ◽  
Mujahid Abbas ◽  
Stojan Radenović
Keyword(s):  
Time Complexity ◽  
Complexity Algorithm

O(2.983n) Time Complexity Algorithm for Optimal Coalition Structure Generation

2011 ◽  
Vol 22 (5) ◽  
pp. 938-950
Author(s):  
Jing-Lei LIU ◽  
Wei ZHANG ◽  
Xiang-Rong TONG ◽  
Zhen-Rong ZHANG
Keyword(s):  
Time Complexity ◽  
Coalition Structure ◽  
Structure Generation ◽  
Coalition Structure Generation ◽  
Complexity Algorithm
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