Affiliation:
1. RMIT University, Melbourne, Victoria, Australia
Abstract
Many applications depend on efficient management of large sets of distinct strings in memory. For example, during index construction for text databases a record is held for each distinct word in the text, containing the word itself and information such as counters. We propose a new data structure, the burst trie, that has significant advantages over existing options for such applications: it uses about the same memory as a binary search tree; it is as fast as a trie; and, while not as fast as a hash table, a burst trie maintains the strings in sorted or near-sorted order. In this paper we describe burst tries and explore the parameters that govern their performance. We experimentally determine good choices of parameters, and compare burst tries to other structures used for the same task, with a variety of data sets. These experiments show that the burst trie is particularly effective for the skewed frequency distributions common in text collections, and dramatically outperforms all other data structures for the task of managing strings while maintaining sort order.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications,General Business, Management and Accounting,Information Systems
Reference56 articles.
1. Aho A. V. Hopcroft J. E. and Ullman J. D. 1983. Data Structures and Algorithms. Addison-Wesley Reading Massachusetts. Aho A. V. Hopcroft J. E. and Ullman J. D. 1983. Data Structures and Algorithms. Addison-Wesley Reading Massachusetts.
2. Aho A. V. Sethi R. and Ullman J. D. 1986. Compilers Principle Techniques and Tools. Addison-Wesley Reading Massachusetts. Aho A. V. Sethi R. and Ullman J. D. 1986. Compilers Principle Techniques and Tools. Addison-Wesley Reading Massachusetts.
3. Algorithms for trie compaction
4. Improved behaviour of tries by adaptive branching
5. An efficient implementation of trie structures
Cited by
98 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献