ITR: Grammar-based Graph Compression Supporting Fast Triple Queries
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866913539550085120 |
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| author | Adler, Enno Böttcher, Stefan Hartel, Rita |
| author_facet | Adler, Enno Böttcher, Stefan Hartel, Rita |
| contents | Neighborhood queries and triple queries are the most common queries on graphs; thus, it is desirable to answer them efficiently on compressed data structures. We present a compression scheme called Incidence-Type-RePair (ITR) for graphs with labeled nodes and labeled edges based on RePair and apply the scheme to network, version, and RDF graphs. We show that ITR performs neighborhood queries and triple queries within only a few milliseconds and thereby outperforms existing RePair-based solutions on graphs while providing a compression size comparable to existing graph compressors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_01028 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | ITR: Grammar-based Graph Compression Supporting Fast Triple Queries Adler, Enno Böttcher, Stefan Hartel, Rita Databases Neighborhood queries and triple queries are the most common queries on graphs; thus, it is desirable to answer them efficiently on compressed data structures. We present a compression scheme called Incidence-Type-RePair (ITR) for graphs with labeled nodes and labeled edges based on RePair and apply the scheme to network, version, and RDF graphs. We show that ITR performs neighborhood queries and triple queries within only a few milliseconds and thereby outperforms existing RePair-based solutions on graphs while providing a compression size comparable to existing graph compressors. |
| title | ITR: Grammar-based Graph Compression Supporting Fast Triple Queries |
| topic | Databases |
| url | https://arxiv.org/abs/2306.01028 |