Practical algorithms for transposition-invariant string-matching

Abstract We consider the problems of (1) longest common subsequence (LCS) of two given strings in the case where the first may be shifted by some constant (that is, transposed) to match the second, and (2) transposition-invariant text searching using indel distance. These problems have applications in music comparison and retrieval. We introduce two novel techniques to solve these problems efficiently. The first is based on the branch and bound method, the second on bit-parallelism. Our branch and bound algorithm computes the longest common transposition-invariant subsequence (LCTS) in time O ( ( m 2 + log log σ ) log σ ) in the best case and O ( ( m 2 + log σ ) σ ) in the worst case, where m and σ, respectively, are the length of the strings and the size of the alphabet. On the other hand, we show that the same problem can be solved by using bit-parallelism and thus obtain a speedup of O ( w / log m ) over the classical algorithms, where the computer word has w bits. The advantage of this latter algorithm over the present bit-parallel ones is that it allows the use of more complex distances, including general integer weights. Since our branch and bound method is very flexible, it can be further improved by combining it with other efficient algorithms such as our novel bit-parallel algorithm. We experiment on several combination possibilities and discuss which are the best settings for each of those combinations. Our algorithms are easily extended to other musically relevant cases, such as δ-matching and polyphony (where there are several parallel texts to be considered). We also show how our bit-parallel algorithm is adapted to text searching and illustrate its effectiveness in complex cases where the only known competing method is the use of brute force.

[1]  Hanan Samet,et al.  Distance browsing in spatial databases , 1999, TODS.

[2]  Dan Gusfield,et al.  Algorithms on Strings, Trees, and Sequences - Computer Science and Computational Biology , 1997 .

[3]  Maxime Crochemore,et al.  A fast and practical bit-vector algorithm for the Longest Common Subsequence problem , 2001, Inf. Process. Lett..

[4]  Esko Ukkonen,et al.  Sweepline the Music! , 2003, Computer Science in Perspective.

[5]  Gonzalo Navarro,et al.  Bit-Parallel Branch and Bound Algorithm for Transposition Invariant LCS , 2004, SPIRE.

[6]  Kjell Lemström,et al.  Musical Information Retrieval Using Musical Parameters , 1998, ICMC.

[7]  Eugene W. Myers,et al.  A fast bit-vector algorithm for approximate string matching based on dynamic programming , 1998, JACM.

[8]  Anne Bergeron,et al.  Vector Algorithms for Approximate String Matching , 2002, Int. J. Found. Comput. Sci..

[9]  Esko Ukkonen,et al.  Including Interval Encoding into Edit Distance Based Music Comparison and Retrieval , 2003 .

[10]  Gonzalo Navarro,et al.  Algorithms for Transposition Invariant String Matching , 2003, STACS.

[11]  Emilios Cambouropoulos,et al.  A general pitch interval representation: Theory and applications , 1996 .

[12]  Wojciech Rytter,et al.  Text Algorithms , 1994 .

[13]  Gonzalo Navarro,et al.  Flexible and Efficient Bit-Parallel Techniques for Transposition Invariant Approximate Matching in Music Retrieval , 2003, SPIRE.

[14]  Jorma Tarhio,et al.  Transposition Invariant Pattern Matching for Multi-Track Strings , 2003, Nord. J. Comput..

[15]  Rolf Klein,et al.  Computer Science in Perspective: Essays Dedicated to Thomas Ottmann , 2003 .

[16]  Geraint A. Wiggins,et al.  SIA(M)ESE: An efficient algorithm for transposition invariant pattern matching in multidimensional datasets , 2001 .

[17]  Gonzalo Navarro,et al.  A bit-parallel suffix automaton approach for (δ, γ)-matching in music retrieval , 2003 .

[18]  Gonzalo Navarro,et al.  Faster Bit-Parallel Approximate String Matching , 2002, CPM.