Combining Graph Exploration and Fragmentation for Scalable RDF Query Processing

Khelil, Abdallah; Mesmoudi, Amin; Galicia, Jorge; Bellatreche, Ladjel; Hacid, Mohand-Saïd; Coquery, Emmanuel

doi:10.1007/s10796-020-09998-z

Cited by 5 publications

(1 citation statement)

References 27 publications

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“…In gStore, each entity node is signed (Signature) and encoded, a binary-based signature graph (Signature Graph) is constructed, and a VS-tree index is established on this basis, the search space is reduced. A novel approach is proposed to perform queries (Basic Graph Patterns, Wildcards, Aggregations and Sorting) on RDF data (Khelil, A., et al 2021). RDF graph exploration is combined with physical fragmentation of triples.…”

Section: Related Workmentioning

confidence: 99%

Large-Scale Commodity Knowledge Organization and Intelligent Query Optimization

2022

International Journal of Mobile Computing and Multimedia Communications

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The Internet is facing the era of knowledge interconnection Web3.0, and its goal is to realize a more intelligent network that can be understood by both humans and machines. In this environment, various types of knowledge graphs have emerged. Because of the heterogeneity of knowledge, commodity knowledge makes its management more challenging. A large-scale product knowledge organization framework is designed, objective product classification knowledge is combined with subjective user perspectives in the framework, a neural network-based learning index technology is proposed to improve query efficiency. According to the properties of the knowledge structure and the characteristics of query requirements, a connection strategy is realized based on sub-variable combination.The experimental results show that, compared with the existing knowledge management system, the proposed method has a significant improvement in the retrieval efficiency of large-scale commodity knowledge.

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Section: Related Workmentioning

confidence: 99%