2020
Journal article  Open Access

Techniques for inverted index compression

Pibiri G. E., Venturini R.

Information Retrieval (cs.IR)  Compression  efficiency  Computer Science - Information Retrieval  FOS: Computer and information sciences  inverted index  Efficiency  Theoretical Computer Science  General Computer Science  compression  Inverted index 

The data structure at the core of large-scale search engines is the inverted index, which is essentially a collection of sorted integer sequences called inverted lists. Because of the many documents indexed by such engines and stringent performance requirements imposed by the heavy load of queries, the inverted index stores billions of integers that must be searched efficiently. In this scenario, index compression is essential because it leads to a better exploitation of the computer memory hierarchy for faster query processing and, at the same time, allows reducing the number of storage machines. The aim of this article is twofold: first, surveying the encoding algorithms suitable for inverted index compression and, second, characterizing the performance of the inverted index through experimentation.

Source: ACM computing surveys 53 (2020). doi:10.1145/3415148

Publisher: Association for Computing Machinery,, New York, N.Y. , Stati Uniti d'America


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BibTeX entry
@article{oai:it.cnr:prodotti:435494,
	title = {Techniques for inverted index compression},
	author = {Pibiri G. E. and Venturini R.},
	publisher = {Association for Computing Machinery,, New York, N.Y. , Stati Uniti d'America},
	doi = {10.1145/3415148 and 10.48550/arxiv.1908.10598},
	journal = {ACM computing surveys},
	volume = {53},
	year = {2020}
}

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