Abstract
Currently, there are numerous knowledge retrieval systems available to researchers, among which the RDF retrieval system is the most common. However, in practice, these systems are often plagued with problems, such as long index constructions and loading times and require large amounts of disk storage space, which are faults that make the system non-conducive to the dynamic incremental updates of data. This paper proposes a scalable lightweight RDF retrieval system, which has the following characteristics: 1) optimization of the index structure to reduce disk occupation and speed up the construction; 2) query optimizations based on query strategy selection; and 3) an interactive visual operation interface. The final evaluation results show that our system uses less disk space and has faster index construction times, and the query performance is competitive with the latest RDF retrieval systems.
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Acknowledgment
This work was supported by National Natural Science Foundation of China (Nos. 62062027, U1811264), Guangxi Natural Science Foundations (No. 2018GXNSFDA281049), the Science and Technology Major Project of Guangxi Province (No. AA19046004), the Innovation Project of GUET Graduate Education (No. 2021YCXS052), the project of Guangxi Key Laboratory of Trusted Software.
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Lin, Y., Fang, C., Jiang, Y., Li, Y. (2022). A Scalable Lightweight RDF Knowledge Retrieval System. In: Bhattacharya, A., et al. Database Systems for Advanced Applications. DASFAA 2022. Lecture Notes in Computer Science, vol 13247. Springer, Cham. https://doi.org/10.1007/978-3-031-00129-1_44
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DOI: https://doi.org/10.1007/978-3-031-00129-1_44
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