The problem of computing similarity of two run-length encoded strings has been studied for various scoring metrics. Many algorithms have been developed for the longest common subsequence metric and some algorithms for the Levenshtein distance metric and the weighted edit distance metric. In this paper we consider similarity based on the affine gap penalty metric which is a more general and rather complicated scoring metric than the weighted edit distance. To compute similarity in this model efficiently, we convert the problem to a path problem on a directed acyclic graph and use some properties of maximum paths in this graph. We present an O(nm′ + n′m) time algorithm for computing similarity of two run-length encoded strings in the affine gap penalty model, where n′ and m′ are the lengths of given two runlength encoded strings, and n and m are the decoded lengths of given two strings, respectively.
|Title of host publication||String Processing and Information Retrieval - 12th International Conference, SPIRE 2005, Proceedings|
|Number of pages||12|
|ISBN (Print)||3540297405, 9783540297406|
|State||Published - 2005|
|Event||12th International Conference on String Processing and Information Retrieval, SPIRE 2005 - Buenos Aires, Argentina|
Duration: 2 Nov 2005 → 4 Nov 2005
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||12th International Conference on String Processing and Information Retrieval, SPIRE 2005|
|Period||2/11/05 → 4/11/05|
Bibliographical noteFunding Information:
I K. Park’s work was supported by FPR05A2-341 of 21C Frontier Functional Proteomics Project from Korean Ministry of Science & Technology and A. Amir and G. M. Landau’s work was partially supported by the Israel Science Foundation grant 35/05. ∗Corresponding author. Tel.: +82 2 880 8381; fax: +82 2 885 3141. E-mail address: firstname.lastname@example.org (K. Park).
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science (all)