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Link to original content: https://doi.org/10.1007/978-3-319-19929-0_19
LZD Factorization: Simple and Practical Online Grammar Compression with Variable-to-Fixed Encoding | SpringerLink
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LZD Factorization: Simple and Practical Online Grammar Compression with Variable-to-Fixed Encoding

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Combinatorial Pattern Matching (CPM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9133))

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Abstract

We propose a new variant of the LZ78 factorization which we call the LZ Double-factor factorization (LZD factorization). Each factor of the LZD factorization of a string is the concatenation of the two longest previous factors, while each factor of the LZ78 factorization is that of the longest previous factor and the following character. Interestingly, this simple modification drastically improves the compression ratio in practice. We propose two online algorithms to compute the LZD factorization in \(O(m (M + \min (m, M)\log \sigma ))\) time and \(O(m)\) space, or in \(O(N \log \sigma )\) time and \(O(N)\) space, where \(m\) is the number of factors to output, \(M\) is the length of the longest factor(s), \(N\) is the length of the input string, and \(\sigma \) is the alphabet size. We also show two versions of our LZD factorization with variable-to-fixed encoding, and present online algorithms to compute these versions in \(O(N + \min (m, 2^L) (M + \min (m, M, 2^L) \log \sigma ))\) time and \(O(\min (2^L, m))\) space, where \(L\) is the bit-length of each fixed-length code word. The LZD factorization and its versions with variable-to-fixed encoding are actually grammar-based compression, and our experiments show that our algorithms outperform the state-of-the-art online grammar-based compression algorithms on several data sets.

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Notes

  1. 1.

    The bound \(M = O(N)\) can be achieved with string \(a^{N-1}\)$ with \(N-1 = 2^k\) for some \(k\). Observe that \(f_1 = aa\), \(f_2 = f_1f_1 = aaaa\), \(\ldots \), \(f_{m-1} = a^{\frac{N-1}{2}}\), and \(f_{m} = \)$.

  2. 2.

    Source codes are available at https://github.com/kg86/lzd.

  3. 3.

    The number of characters the algorithm can process a second.

  4. 4.

    http://pizzachili.dcc.uchile.cl/texts.html.

  5. 5.

    http://pizzachili.dcc.uchile.cl/repcorpus.html.

  6. 6.

    The first 10 GB of enwiki-20150112-pages-meta-history1.xml-p000000010p000002983.7z, downloaded from http://dumps.wikimedia.org/backup-index.html.

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Acknowledgements

We would like to thank Shirou Maruyama and Takuya Kida for providing source codes of their compression programs FOLCA and ADS.

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Correspondence to Keisuke Goto .

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Goto, K., Bannai, H., Inenaga, S., Takeda, M. (2015). LZD Factorization: Simple and Practical Online Grammar Compression with Variable-to-Fixed Encoding. In: Cicalese, F., Porat, E., Vaccaro, U. (eds) Combinatorial Pattern Matching. CPM 2015. Lecture Notes in Computer Science(), vol 9133. Springer, Cham. https://doi.org/10.1007/978-3-319-19929-0_19

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  • DOI: https://doi.org/10.1007/978-3-319-19929-0_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19928-3

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