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Efficient Inverted Index Compression Algorithm Characterized by Faster Decompression Compared with the Golomb-Rice

Andrzej Chmielowiec1, Paweł Litwin2

  • 1The Faculty of Mechanics and Technology, Rzeszow University of Technology, Kwiatkowskiego 4, 37-450 Stalowa Wola, Poland.

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Summary
This summary is machine-generated.

This study introduces a new coding method for binary sequences with many zeros. It offers faster decompression than Golomb-Rice coding for database applications, with only a slight loss in compression efficiency.

Keywords:
Golomb-Rice codinginverted index compressionruns codingsparse binary sequence compression

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Area of Science:

  • Information Theory
  • Computer Science
  • Data Compression

Background:

  • Binary sequences with a fixed number of ones are common in data storage and retrieval.
  • Existing compression methods like Golomb-Rice coding can be slow for decompression, especially in database applications.

Purpose of the Study:

  • To propose a novel compression algorithm for binary sequences with a disproportionate number of zeros and ones.
  • To develop a method that prioritizes decompression speed over maximal compression ratio.

Main Methods:

  • Derivation of entropy bounds for binary sequences with a fixed number of ones: k log2(0.48·n/k) < H < k log2(2.72·n/k).
  • Development of a simple fixed-length word coding scheme based on the derived entropy bounds.

Main Results:

  • The proposed coding method achieves efficient compression for binary sequences with a high number of zeros.
  • Decompression speed is significantly improved compared to Golomb-Rice coding.
  • A minor reduction in compression efficiency is observed, which is acceptable for specific applications.

Conclusions:

  • The developed algorithm provides a practical solution for compressing sparse binary data.
  • This method is particularly beneficial for database applications where rapid data retrieval is critical.