Efficient Rank/Select Data Structures for Large-Alphabet Strings

Grunnleggende konsepter

This paper introduces a compressed data structure that supports the fundamental operations of rank and select efficiently on large-alphabet strings.

Sammendrag

The paper focuses on engineering efficient implementations of the alphabet-partitioning approach for supporting rank and select operations on large-alphabet strings. The main contributions are:

The authors carry out algorithm engineering on the alphabet-partition approach by Barbay et al. [15], obtaining an implementation that uses compressed space while supporting operations s.rank and s.select efficiently in practice. Their approach also yields interesting theoretical trade-offs.

The authors show that their approach yields competitive trade-offs when used for (i) snippet extraction from text databases and (ii) intersection of inverted lists, which are key operations for modern information retrieval systems.

The authors show that the alphabet-partition approach can be used to improve run-length compression of large-alphabet strings formed by r equal-symbol runs. They introduce a competitive alternative both in theory and practice.

The authors show that their alphabet-partitioning scheme can be efficiently implemented on a distributed-memory system.

The authors' implementation of alphabet partitioning is effective and efficient for supporting the fundamental rank and select operations, as well as for supporting several key operations in modern information retrieval systems that manipulate large-alphabet strings.

Statistikk

The paper does not contain any explicit numerical data or statistics. The focus is on the algorithmic and engineering aspects of the proposed data structure.

Sitater

The paper does not contain any direct quotes that are particularly striking or support the key arguments.

Viktige innsikter hentet fra

Engineering Rank/Select Data Structures for Large-Alphabet Strings

by Dieg... klokken arxiv.org 05-03-2024

https://arxiv.org/pdf/2305.14461.pdf

Dypere Spørsmål

How can the proposed data structure be extended or adapted to support other operations beyond rank and select, such as pattern matching or range queries, on large-alphabet strings

The proposed data structure can be extended to support other operations beyond rank and select by incorporating additional data structures and algorithms. For pattern matching, one approach could be to integrate techniques like suffix arrays or suffix trees to efficiently locate occurrences of a specific pattern within the string. Range queries, on the other hand, could be facilitated by augmenting the data structure with interval tree or segment tree functionalities to quickly identify and retrieve elements within a specified range. By combining these techniques with the existing rank and select operations, the data structure can offer comprehensive support for a wide range of operations on large-alphabet strings.

What are the potential limitations or drawbacks of the alphabet-partitioning approach, and how could they be addressed in future work

One potential limitation of the alphabet-partitioning approach is the trade-off between space efficiency and query performance. While the approach excels in compressing the data and supporting rank/select operations efficiently, it may struggle with certain types of queries that require complex processing or involve extensive traversal of the data structure. To address this limitation, future work could focus on optimizing the data structure for specific query types, implementing caching mechanisms to improve query response times, or exploring hybrid approaches that combine alphabet partitioning with other data structures to enhance overall performance. Additionally, research could be conducted to investigate the scalability of the approach for even larger alphabets and strings.

What other real-world applications, beyond information retrieval, could benefit from the efficient rank/select data structures for large-alphabet strings introduced in this paper

Beyond information retrieval, the efficient rank/select data structures for large-alphabet strings introduced in this paper could benefit various real-world applications. One such application is bioinformatics, where DNA sequences are represented as large-alphabet strings and operations like pattern matching and sequence alignment are crucial for genetic analysis. Additionally, in computational linguistics, natural language processing tasks such as text classification, sentiment analysis, and named entity recognition could leverage these data structures for efficient processing of text data with diverse character sets. Furthermore, in data compression and encoding, the ability to efficiently handle large-alphabet strings can enhance the performance of compression algorithms and encoding schemes used in multimedia applications and data storage systems.