BIDIRECTIONAL SEARCH IN A STRING USING WAVELET MATRIX AND BURROWS WHEELER TRANSFORM

BIDIRECTIONAL SEARCH IN A STRING USING WAVELET MATRIX AND BURROWS WHEELER TRANSFORM

Abstract:
The efficient search and retrieval of information within large strings or texts are fundamental challenges in various fields, including bioinformatics, text mining, and data compression. Bidirectional search algorithms have emerged as powerful tools to address these challenges. This abstract presents a novel approach that combines the wavelet matrix and Burrows-Wheeler Transform (BWT) to enable bidirectional search in a string efficiently.

The wavelet matrix is a data structure that allows for efficient rank and select operations on strings. It provides an effective representation of the input text, enabling rapid access to substring information. On the other hand, the Burrows-Wheeler Transform is a reversible text transformation that rearranges characters in a string to improve compression and facilitate pattern matching.

In our approach, we leverage the strengths of both the wavelet matrix and the BWT to perform bidirectional search in a string. We construct the wavelet matrix on the input text, which enables us to efficiently compute rank and select operations. Then, we apply the Burrows-Wheeler Transform to the wavelet matrix to achieve enhanced pattern matching capabilities.

To perform a bidirectional search, we start from both ends of the string simultaneously and iteratively refine the search space by utilizing the rank and select operations provided by the wavelet matrix. By combining the bidirectional approach with the pattern matching capabilities of the BWT, we can efficiently locate patterns within the string in a time-efficient manner.

Our experimental results demonstrate the effectiveness of the proposed approach in terms of both search time and space efficiency. The bidirectional search using the wavelet matrix and Burrows-Wheeler Transform outperforms existing methods, providing faster and more accurate pattern matching results.

In conclusion, our study presents a novel approach for bidirectional search in a string by combining the wavelet matrix and Burrows-Wheeler Transform. The integration of these techniques enables efficient pattern matching and retrieval of information within large strings. This research contributes to the advancement of search algorithms for various applications, including bioinformatics, text mining, and data compression.

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