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DEFLATE Compressed Data Format Specification version 1.3", RFC
, 1951
"... This memo provides information for the Internet community. This memo does not specify an Internet standard of any kind. Distribution of this memo is unlimited. IESG Note: The IESG takes no position on the validity of any Intellectual Property Rights statements contained in this document. ..."
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Cited by 168 (0 self)
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This memo provides information for the Internet community. This memo does not specify an Internet standard of any kind. Distribution of this memo is unlimited. IESG Note: The IESG takes no position on the validity of any Intellectual Property Rights statements contained in this document.
Data Compression
 ACM Computing Surveys
, 1987
"... This paper surveys a variety of data compression methods spanning almost forty years of research, from the work of Shannon, Fano and Huffman in the late 40's to a technique developed in 1986. The aim of data compression is to reduce redundancy in stored or communicated data, thus increasing effectiv ..."
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Cited by 87 (3 self)
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This paper surveys a variety of data compression methods spanning almost forty years of research, from the work of Shannon, Fano and Huffman in the late 40's to a technique developed in 1986. The aim of data compression is to reduce redundancy in stored or communicated data, thus increasing effective data density. Data compression has important application in the areas of file storage and distributed systems. Concepts from information theory, as they relate to the goals and evaluation of data compression methods, are discussed briefly. A framework for evaluation and comparison of methods is constructed and applied to the algorithms presented. Comparisons of both theoretical and empirical natures are reported and possibilities for future research are suggested. INTRODUCTION Data compression is often referred to as coding, where coding is a very general term encompassing any special representation of data which satisfies a given need. Information theory is defined to be the study of eff...
Fast and Flexible Word Searching on Compressed Text
, 2000
"... ... text. When searching complex or approximate patterns, our algorithms are up to 8 times faster than the search on uncompressed text. We also discuss the impact of our technique in inverted files pointing to logical blocks and argue for the possibility of keeping the text compressed all the time, ..."
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Cited by 81 (33 self)
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... text. When searching complex or approximate patterns, our algorithms are up to 8 times faster than the search on uncompressed text. We also discuss the impact of our technique in inverted files pointing to logical blocks and argue for the possibility of keeping the text compressed all the time, decompressing only for displaying purposes.
Efficient Decoding of Prefix Codes
 Communications of the ACM
, 1990
"... We discuss representations of prefix codes and the corresponding storage space and decoding time requirements. We assume that a dictionary of words to be encoded has been defined and that a prefix code appropriate to the dictionary has been constructed. The encoding operation becomes simple given th ..."
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Cited by 31 (0 self)
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We discuss representations of prefix codes and the corresponding storage space and decoding time requirements. We assume that a dictionary of words to be encoded has been defined and that a prefix code appropriate to the dictionary has been constructed. The encoding operation becomes simple given these assumptions and given an appropriate parsing strategy, therefore we concentrate on decoding. The application which led us to this work constrains the use of internal memory during the decode operation. As a result, we seek a method of decoding which has a small memory requirement. Introduction Data compression is an important and muchstudied problem. Compressing data to be stored or transmitted can result in significant improvements in the use of computing resources. The degree of improvement that can be achieved depends not only on the selection of a data compression method, but also on the characteristics of the particular application. That is, no single data compression algorithm wi...
Fast Searching on Compressed Text Allowing Errors
, 1998
"... We present a fast compression and decompression scheme for natural language texts that allows efficient and flexible string matching by searching the compressed text directly. The compression scheme uses a wordbased Huffman encoding and the coding alphabet is byteoriented rather than bitoriented. ..."
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Cited by 25 (15 self)
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We present a fast compression and decompression scheme for natural language texts that allows efficient and flexible string matching by searching the compressed text directly. The compression scheme uses a wordbased Huffman encoding and the coding alphabet is byteoriented rather than bitoriented. We compress typical English texts to about 30% of their original size, against 40% and 35% for Compress and Gzip, respectively. Compression times are close to the times of Compress and approximately half the times of Gzip, and decompression times are lower than those of Gzip and one third of those of Compress. The searching algorithm allows a large number of variations of the exact and approximate compressed string matching problem, such as phrases, ranges, complements, wild cards and arbitrary regular expressions. Separators and stopwords can be discarded at search time without significantly increasing the cost. The algorithm is based on a wordoriented shiftor algorithm and a fast BoyerMooretype filter. It concomitantly uses the vocabulary of the text available as part of the Huffman coding data. When searching for simple patterns, our experiments show that running our algorithm on a compressed text is twice as fast as running Agrep on the uncompressed version of the same text. When searching complex or approximate patterns, our algorithm is up to 8 times faster than Agrep. We also mention the impact of our technique in inverted files pointing to documents or logical blocks as Glimpse.
Is Huffman Coding Dead?
 Computing
, 1993
"... : In recent publications about data compression, arithmetic codes are often suggested as the state of the art, rather than the more popular Huffman codes. While it is true that Huffman codes are not optimal in all situations, we show that the advantage of arithmetic codes in compression performance ..."
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Cited by 17 (3 self)
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: In recent publications about data compression, arithmetic codes are often suggested as the state of the art, rather than the more popular Huffman codes. While it is true that Huffman codes are not optimal in all situations, we show that the advantage of arithmetic codes in compression performance is often negligible. Referring also to other criteria, we conclude that for many applications, Huffman codes should still remain a competitive choice. 1. Introduction It is paradoxical that, as the technology for storing and transmitting information has gotten cheaper and more effective, interest in data compression has increased. There are many explanations, but most conspicuous is that improvements in media have expanded our sense of what we wish to store. For example, CDRom technology allows us to store whole libraries instead of records describing individual items; but the requirements of storing full text easily exceeds the capabilities even of the optical format. Similarly, there is ...
Bounding the Depth of Search Trees
 The Computer Journal
, 1993
"... For an ordered sequence of n weights, Huffman's algorithm constructs in time and space O(n) a search tree with minimum average path length, or, which is equivalent, a minimum redundancy code. However, if an upper bound B is imposed on the length of the codewords, the best known algorithms for the co ..."
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Cited by 16 (5 self)
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For an ordered sequence of n weights, Huffman's algorithm constructs in time and space O(n) a search tree with minimum average path length, or, which is equivalent, a minimum redundancy code. However, if an upper bound B is imposed on the length of the codewords, the best known algorithms for the construction of an optimal code have time and space complexities O(Bn 2 ). A new algorithm is presented, which yields suboptimal codes, but in time O(n log n) and space O(n). Under certain conditions, these codes are shown to be close to optimal, and extensive experiments suggest that in many practical applications, the deviation from the optimum is negligible. 1. Motivation and Introduction We consider the set B(n; b) of extended binary trees with n leaves, labelled 1 to n, and with depth b, henceforth called brestricted trees. An extended binary tree is a binary tree in which every internal node has two sons (here, and in what follows, we use the terminology of Knuth [16, pp. 399...
Skeleton Trees for the Efficient Decoding of Huffman Encoded Texts
 Information Retrieval
, 1997
"... : A new data structure is investigated, which allows fast decoding of texts encoded by canonical Huffman codes. The storage requirements are much lower than for conventional Huffman trees, O(log 2 n) for trees of depth O(log n), and decoding is faster, because a part of the bitcomparisons nec ..."
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Cited by 10 (4 self)
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: A new data structure is investigated, which allows fast decoding of texts encoded by canonical Huffman codes. The storage requirements are much lower than for conventional Huffman trees, O(log 2 n) for trees of depth O(log n), and decoding is faster, because a part of the bitcomparisons necessary for the decoding may be saved. Empirical results on large reallife distributions show a reduction of up to 50% and more in the number of bit operations. The basic idea is then generalized, yielding further savings. This is an extended version of a paper which has been presented at the 8th Annual Symposium on Combinatorial Pattern Matching (CPM'97), and appeared in its proceedings, pp. 6575.  1  1.
Bidirectional Huffman Coding
, 1989
"... Under what conditions can Huffman codes be efficiently decoded in both directions? The usual decoding procedure works also for backward decoding only if the code has the affix property, i.e., both prefix and suffix properties. Some affix Huffman codes are exhibited, and necessary conditions for the ..."
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Cited by 10 (2 self)
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Under what conditions can Huffman codes be efficiently decoded in both directions? The usual decoding procedure works also for backward decoding only if the code has the affix property, i.e., both prefix and suffix properties. Some affix Huffman codes are exhibited, and necessary conditions for the existence of such codes are given. An algorithm is presented which, for a given set of codeword lengths, constructs an affix code, if there exists one. Since for many distributions there is no affix code giving the same compression as the Huffman code, a new algorithm for backward decoding of nonaffix Huffman codes is presented, and its worst case complexity is proved to be linear in the length of the encoded text. 1. Introduction For a given sequence of n weights w 1 ; : : : ; wn , with w i ? 0, Huffman's wellknown algorithm [9] constructs an optimum prefix code. We use throughout the term `code' as abbreviation for `set of codewords'. In a prefix code no codeword is the prefix of any o...