A proper fusion of complex data is of interest to many researchers in diverse fields, including
computational statistics, computational geometry, bioinformatics, machine learning, pattern …

String problems arise in various applications ranging from text mining to biological
sequence analysis. Many string problems are NP-hard. This motivates the search for (fixed …

This paper aims to present a new genetic approach that uses rank distance for solving two
known NP-hard problems, and to compare rank distance with other distance measures for …

This paper aims to present several clustering methods based on rank distance. Rank
distance has applications in many different fields such as computational linguistics, biology …

This paper aims to present two clustering methods based on rank distance. The K-means
algorithm represents each cluster by a single mean vector. The mean vector is computed …

This paper aims to present two clustering methods based on rank distance. Rank distance
has applications in many different fields such as computational linguistics, biology and …

Given a set W of k strings of length n over an alphabet\varSigma Σ, the center string of W is
defined as the string w such that the maximum distance to w of all strings in W is minimized …

String variables occur as a natural part of many computationally challenging problems from
different areas, such as computational biology (eg, protein folding, sequence alignment) …

Given a finite set S of strings of length m, the task of finding a string t that minimizes the
Hamming distance from t to S, has wide applications. This paper presents a two-phase Ant …

Abstract The Closest String Problem (CSP) calls for finding an n-string that minimizes its
maximum distance from m given n-strings. Integer linear programming (ILP) proved to be …