Difference between revisions of "数据管理小组"
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# 王鑫, 邹磊, 王朝坤, 彭鹏. 知识图谱构建技术综述[J]. 软件学报, 30(7):1000-9825, 2019. [http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=2&SID=5A8ngFeHmXRHcuUqaNS&page=1&doc=1] | # 王鑫, 邹磊, 王朝坤, 彭鹏. 知识图谱构建技术综述[J]. 软件学报, 30(7):1000-9825, 2019. [http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&qid=2&SID=5A8ngFeHmXRHcuUqaNS&page=1&doc=1] | ||
# Besta M, Peter E, Gerstenberger R, et al. Demystifying graph databases: Analysis and taxonomy of data organization, system designs, and graph queries[J]. arXiv preprint arXiv:1910.09017, 2019. [https://arxiv.org/abs/1910.09017] | # Besta M, Peter E, Gerstenberger R, et al. Demystifying graph databases: Analysis and taxonomy of data organization, system designs, and graph queries[J]. arXiv preprint arXiv:1910.09017, 2019. [https://arxiv.org/abs/1910.09017] | ||
+ | |||
== 子图匹配查询相关 == | == 子图匹配查询相关 == | ||
# A. K. Chandra, P. M. Merlin, Optimal implementation of conjunctive queries in relational databases, in ACM Symposium on Theory of Computing, pp.77–90, 1997. [https://dl.acm.org/doi/abs/10.1145/800105.803397] | # A. K. Chandra, P. M. Merlin, Optimal implementation of conjunctive queries in relational databases, in ACM Symposium on Theory of Computing, pp.77–90, 1997. [https://dl.acm.org/doi/abs/10.1145/800105.803397] | ||
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# I. Abdelaziz, R. Harbi, Z. Khayyat, and P. Kalnis. A Survey and Experimental Comparison of Distributed SPARQL Engines for Very Large RDF Data. PVLDB, 10(13):2049–2060, 2017. [https://dl.acm.org/doi/abs/10.14778/3151106.3151109] | # I. Abdelaziz, R. Harbi, Z. Khayyat, and P. Kalnis. A Survey and Experimental Comparison of Distributed SPARQL Engines for Very Large RDF Data. PVLDB, 10(13):2049–2060, 2017. [https://dl.acm.org/doi/abs/10.14778/3151106.3151109] | ||
# Yang Z, Lai L, Lin X, et al. Huge: An efficient and scalable subgraph enumeration system[J]. arXiv preprint arXiv:2103.14294, 2021.[https://arxiv.org/pdf/2103.14294.pdf] | # Yang Z, Lai L, Lin X, et al. Huge: An efficient and scalable subgraph enumeration system[J]. arXiv preprint arXiv:2103.14294, 2021.[https://arxiv.org/pdf/2103.14294.pdf] | ||
+ | == 编码 == | ||
+ | # Singh G, Upadhyay D, Atre M. Efficient RDF dictionaries with B+ trees[C]//Proceedings of the ACM India Joint International Conference on Data Science and Management of Data. 2018: 128-136.[https://cse.iitk.ac.in/users/atrem/papers/cods-comad2018.pdf] | ||
+ | # Urbani J, Dutta S, Gurajada S, et al. KOGNAC: efficient encoding of large knowledge graphs[J]. arXiv preprint arXiv:1604.04795, 2016.[https://arxiv.org/pdf/1604.04795.pdf] | ||
+ | == 分布式数据管理 == | ||
+ | # Gurajada S, Seufert S, Miliaraki I, et al. TriAD: a distributed shared-nothing RDF engine based on asynchronous message passing[C]//Proceedings of the 2014 ACM SIGMOD international conference on Management of data. 2014: 289-300.[http://resources.mpi-inf.mpg.de/d5/triad/mod375-gurajada.pdf] | ||
+ | # Schätzle A, Przyjaciel-Zablocki M, Skilevic S, et al. S2RDF: RDF querying with SPARQL on spark[J]. arXiv preprint arXiv:1512.07021, 2015.[https://arxiv.org/pdf/1512.07021.pdf] | ||
+ | # Shao B, Wang H, Li Y. Trinity: A distributed graph engine on a memory cloud[C]//Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. 2013: 505-516.[https://dl.acm.org/doi/pdf/10.1145/2463676.2467799] | ||
+ | # Zeng K, Yang J, Wang H, et al. A distributed graph engine for web scale RDF data[J]. Proceedings of the VLDB Endowment, 2013, 6(4): 265-276.[https://www.graphengine.io/downloads/papers/Trinity.RDF.pdf] | ||
+ | # Zou L, Özsu M T, Chen L, et al. gStore: a graph-based SPARQL query engine[J]. The VLDB journal, 2014, 23(4): 565-590.[https://link.springer.com/article/10.1007/s00778-013-0337-7] | ||
+ | == 索引 == | ||
+ | # Yuan P, Liu P, Wu B, et al. TripleBit: a fast and compact system for large scale RDF data[J]. Proceedings of the VLDB Endowment, 2013, 6(7): 517-528.[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.308.3012&rep=rep1&type=pdf] |
Revision as of 10:18, 5 June 2021
Contents
综述
- Z. Kaoudi and I. Manolescu. RDF in the Clouds: A Survey. VLDB J., 24(1):67–91, 2015. [1]
- Özsu, M. Tamer. "A survey of RDF data management systems." Frontiers of Computer Science 10(3): 418-432, 2016.[2]
- 邹磊, 彭鹏. 分布式 RDF 数据管理综述[J]. 计算机研究与发展, 54(6):1213-1224, 2017.[3]
- I. Abdelaziz, R. Harbi, Z. Khayyat, P. Kalnis, A survey and experimental comparison of distributed SPARQL engines for very large RDF data, Proceedings of the Vldb Endowment 10(13):2049–2060,2017. [4]
- Wylot, Marcin, et al. "RDF Data Storage and Query Processing Schemes: A Survey." ACM Computing Surveys (CSUR) 51(4):84, 2018.[5]
- 王鑫, 邹磊, 王朝坤, 彭鹏. 知识图谱构建技术综述[J]. 软件学报, 30(7):1000-9825, 2019. [6]
- Besta M, Peter E, Gerstenberger R, et al. Demystifying graph databases: Analysis and taxonomy of data organization, system designs, and graph queries[J]. arXiv preprint arXiv:1910.09017, 2019. [7]
子图匹配查询相关
- A. K. Chandra, P. M. Merlin, Optimal implementation of conjunctive queries in relational databases, in ACM Symposium on Theory of Computing, pp.77–90, 1997. [8]
- Z. Sun, H. Wang, H. Wang, B. Shao, J. Li, Efficient subgraph matching on billion node graphs, Proceedings of the VLDB Endowment 5(9):788–799, 2012.[9]
- L. Lai, L. Qin, X. Lin, L. Chang, Scalable subgraph enumeration in MapReduce, Proceedings of the VLDB Endowment 8(10):974–985, 2015. [10]
- # P.Peng,L.Zou, M.T.Özsu, L.Chen, and D.Zhao.Processing SPARQL Queries over Distributed RDF Graphs. VLDB J., 25(2):243–268, 2016. [11]
- L. Lai, L. Qin, X. Lin, Y. Zhang, L. Chang, S. Yang, Scalable distributed subgraph enumeration, Proceedings of the Vldb Endowment 10(3)217–228, 2016. [12]
- I. Abdelaziz, R. Harbi, Z. Khayyat, P. Kalnis, A survey and experimental comparison of distributed SPARQL engines for very large RDF data, Proceedings of the Vldb Endowment 10(13):2049–2060, 2017. [13]
- I. Abdelaziz, R. Harbi, Z. Khayyat, and P. Kalnis. A Survey and Experimental Comparison of Distributed SPARQL Engines for Very Large RDF Data. PVLDB, 10(13):2049–2060, 2017. [14]
- Yang Z, Lai L, Lin X, et al. Huge: An efficient and scalable subgraph enumeration system[J]. arXiv preprint arXiv:2103.14294, 2021.[15]
编码
- Singh G, Upadhyay D, Atre M. Efficient RDF dictionaries with B+ trees[C]//Proceedings of the ACM India Joint International Conference on Data Science and Management of Data. 2018: 128-136.[16]
- Urbani J, Dutta S, Gurajada S, et al. KOGNAC: efficient encoding of large knowledge graphs[J]. arXiv preprint arXiv:1604.04795, 2016.[17]
分布式数据管理
- Gurajada S, Seufert S, Miliaraki I, et al. TriAD: a distributed shared-nothing RDF engine based on asynchronous message passing[C]//Proceedings of the 2014 ACM SIGMOD international conference on Management of data. 2014: 289-300.[18]
- Schätzle A, Przyjaciel-Zablocki M, Skilevic S, et al. S2RDF: RDF querying with SPARQL on spark[J]. arXiv preprint arXiv:1512.07021, 2015.[19]
- Shao B, Wang H, Li Y. Trinity: A distributed graph engine on a memory cloud[C]//Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. 2013: 505-516.[20]
- Zeng K, Yang J, Wang H, et al. A distributed graph engine for web scale RDF data[J]. Proceedings of the VLDB Endowment, 2013, 6(4): 265-276.[21]
- Zou L, Özsu M T, Chen L, et al. gStore: a graph-based SPARQL query engine[J]. The VLDB journal, 2014, 23(4): 565-590.[22]
索引
- Yuan P, Liu P, Wu B, et al. TripleBit: a fast and compact system for large scale RDF data[J]. Proceedings of the VLDB Endowment, 2013, 6(7): 517-528.[23]