Computing Inverse ST in Linear Complexity

Nong, Ge; Zhang, Sen; Chan, Wai Hong

doi:10.1007/978-3-540-69068-9_18

Cited by 8 publications

(23 citation statements)

References 9 publications

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“…We observe a quite similar situation [5], [6] in the Sort Transform (ST) [7], which has been proposed as a finite-order variant of the BWT. The ST, which is also a special case of the GRP transform, was originally developed to speed up the BWT.…”

Section: Introductionmentioning

confidence: 65%

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Extension and Faster Implementation of the GRP Transform for Lossless Compression

Yokoo

2010

Combinatorial Pattern Matching

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Abstract. The GRP transform, or the generalized radix permutation transform was proposed as a parametric generalization of the BWT of the block-sorting data compression algorithm. This paper develops its extension that can be applied with any combination of parameters. By using the technique developed for linear time/space implementation of the sort transform, we propose an efficient implementation for the inverse transformation of the GRP transform. It works for arbitrary parameter values, and can convert the transformed string to the original string in time linear in the string length.

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Section: Introductionmentioning

confidence: 65%

“…The BWT and its variations [6], [7], [8] can be derived from the GRP transform as its special cases. The GRP transform has two parameters: the block length and the context order d, to which we can assign appropriate values so that we can also realize new transforms.…”

Section: Introductionmentioning

confidence: 99%

Extension and Faster Implementation of the GRP Transform for Lossless Compression

Yokoo

2010

Combinatorial Pattern Matching

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“…As T is recovered in reverse sequential order, during the recovery of T , each k-group is processed in reverse sequential order. Fortunately, the context group boundaries (D k ) can be recovered from T k-BWT in O(n) time [20]. To recover T from T k-BWT , the k-group boundaries are recovered first.…”

Section: Text Transformationsmentioning

confidence: 99%

Efficient indexing algorithms for approximate pattern matching in text

Petri

Culpepper

2012

Proceedings of the Seventeenth Australasian Document Computing Symposium

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Approximate pattern matching is an important computational problem with a wide variety of applications in Information Retrieval. Efficient solutions to approximate pattern matching can be applied to natural language keyword queries with spelling mistakes, OCR scanned text incorporated into indexes, language model ranking algorithms based on term proximity, or DNA databases containing sequencing errors. In this paper, we present a novel approach to constructing text indexes capable of efficiently supporting approximate search queries. Our approach relies on a new variant of the Context Bound Burrows-Wheeler Transform (k-BWT), referred to as the Variable Depth Burrows-Wheeler Transform (v-BWT). First, we describe our new algorithm, and show that it is reversible. Next, we show how to use the transform to support efficient text indexing and approximate pattern matching. Lastly, we empirically evaluate the use of the v-BWT for DNA and English text collections, and show a significant improvement in approximate search efficiency over more traditional q-gram based approximate pattern matching algorithms.

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“…After performing LF k , instead of using the row similar to the full BWT, we jump to the last unprocessed row within a given kgroup. To consistently determine the correct context bounds, a bitvector D k is required in order to reconstruct T from [24] or it can be stored with T k-BWT at a cost of n bits. These and other trade-offs are explored in [25].…”

Section: The Burrows-wheeler Transformmentioning

confidence: 99%

Backwards Search in Context Bound Text Transformations

Petri

Navarro

Culpepper

et al. 2011

2011 First International Conference on Data Compression, Communications and Processing

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Abstract-The Burrows-Wheeler Transform (BWT) is the basis for many of the most effective compression and selfindexing methods used today. A key to the versatility of the BWT is the ability to search for patterns directly in the transformed text. A backwards search for a pattern P can be performed on a transformed text by iteratively determining the range of suffixes that match P . The search can be further enhanced by constructing a wavelet tree over the output of the BWT in order to emulate a suffix array. In this paper, we investigate new algorithms for search derived from a variation of the BWT whereby rotations are only sorted to a depth k, commonly referred to as a context bound transform. Interestingly, this BWT variant can be used to mimic a k-gram index, which are used in a variety of applications that need to efficiently return occurrences in text position order. In this paper, we present the first backwards search algorithms on the k-BWT, and show how to construct a self-index containing many of the attractive properties of a k-gram index.

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Computing Inverse ST in Linear Complexity

Cited by 8 publications

References 9 publications

Extension and Faster Implementation of the GRP Transform for Lossless Compression

Extension and Faster Implementation of the GRP Transform for Lossless Compression

Efficient indexing algorithms for approximate pattern matching in text

Backwards Search in Context Bound Text Transformations

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