Open Access
MATEC Web Conf.
Volume 355, 2022
2021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
Article Number 03012
Number of page(s) 12
Section Computing Methods and Computer Application
Published online 12 January 2022
  1. Qin Yi. Research on CPS Testing Technology Facing Environmental Uncertainty[D]. Nanjing University, 2019. [Google Scholar]
  2. Xie JY, Yang J, Chen YG, Wang HX, Yu PS. A sampling-based approach to information recovery. In: Proc. of the ICDE. Iscataway, NJ: IEEE Computer Society, 2008. 476-485. [doi: 10.1109/ICDE.2008.4497456]. [Google Scholar]
  3. Mockus A. Engineering big data solutions. In: Proc. of the Future of Software Engineering. ACM Press, 2014. 85?99. [Google Scholar]
  4. Cai L, Zhu Y. The Challenges of Data Quality and Data Quality Assessment in the Big Data Era. Data Science Journal 2015; 1-10. [Google Scholar]
  5. Jin CQ, Liu HP, Zhou AY. Functional dependency and conditional constraint based data repair. Ruan Jian Xue Bao/Journal of Software, 2016,27(7):1671-1684 (in Chinese). \url{}. [Google Scholar]
  6. Arnaud Castelltort and Anne Laurent. Exploiting NoSQL Graph Databases and in Memory Architectures for Extracting Graph Structural Data Summaries[J]. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2017, 25(1) : 29. [Google Scholar]
  7. Péter Lehotay-Kéry and Attila Kiss. Process, Analyze and Visualize Telecommunication Network Configuration Data in Graph Database[J]. Vietnam Journal of Computer Science, 2020, 07(01) : 12. [Google Scholar]
  8. Chen Ze et al. Research on Automatic Vulnerability Mining Model Based on Knowledge Graph[J]. International Journal on Artificial Intelligence Tools, 2020, 29(07n08). [Google Scholar]
  9. Li JZ, Wang HZ, Gao H. State-of-the-Art of research on big data usability. Ruan Jian Xue Bao/Journal of Software, 2016, 27(7):1605-1625 (in Chinese). \url{}. [Google Scholar]
  10. Hamza Turabieh, Amer Abu Salem, Noor Abu-El-Rub. Dynamic L-RNN recovery of missing data in IoMT applications[J]. Future Generation Computer Systems, 2018,89. [Google Scholar]
  11. M. TALHA, A. ABOU EL KALAM, N. ELMARZOUQI. Big Data: Trade-off between Data Quality and Data Security[J]. Procedia Computer Science, 2019, 151. [Google Scholar]
  12. Danilo Ardagna, Cinzia Cappiello, Walter Samá, Monica Vitali. Context-aware data quality assessment for big data[J]. Future Generation Computer Systems,2018. [Google Scholar]
  13. Maryam Ghasemaghaei, Goran Calic. Can big data improve firm decision quality? The role of data quality and data diagnosticity[J]. Decision Support Systems, 2019, 120. [Google Scholar]
  14. Fan WF, Geerts F. Capturing missing tuples and missing values. In: Proc. of the ACM SIGMOD-SIGACT-SIGART Symp. on Principles of Database Systems. New York: ACM Press, 2010. 169-178. [doi: 10.1145/1807085.1807109]. [Google Scholar]
  15. Fan WF, Geerts F, Lakshmanan LVS, Xiong M. Discovering conditional functional dependencies. IEEE Trans. on Knowledge and Data Engineering, 2011,23(5):683-698. [doi: 10.1109/TKDE.2010.154]. [CrossRef] [Google Scholar]
  16. Bohannon P, Fan WF, Geerts F, Jia X. Conditional functional dependencies for data cleaning. In: Proc. of the ICDE. Piscataway, 2007. 746-755. [doi: 10.1109/ICDE.2007.367920]. [Google Scholar]
  17. Bravo L, Fan WF, Ma S. Extending dependencies with conditions. In: Proc. of the VLDB. 2007. 243-254. [Google Scholar]
  18. Carlo Combi, Pietro Sala. Mining approximate interval-based temporal dependencies[J]. Acta Informatica, 2016, Vol.53 (6-8), pp.547-585. [CrossRef] [Google Scholar]
  19. Jason Van Hulse and Taghi M. Khoshgoftaar and Amri Napolitano. Evaluating the Impact of Data Quality on Sampling[J]. Journal of Information and Knowledge Management, 2011, 10(3) : 225-245. [CrossRef] [Google Scholar]
  20. P. C. SAXENA and D. K. TAYAL. NORMALIZATION IN TYPE-2 FUZZY RELATIONAL DATA MODEL BASED ON FUZZY FUNCTIONAL DEPENDENCY USING FUZZY FUNCTIONS[J]. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2012, 20(1) : 99-138. [CrossRef] [Google Scholar]
  21. Tu FF, Zhou MH. Data quality problems in software development activity data. Ruan Jian Xue Bao/Journal of Software, 2019,30(5):1522?1531 (in Chinese). \url{}. [Google Scholar]
  22. Gong XQ, Jin CQ, Wang XL, Zhang R, Zhou AY. Data-Intensive science and engineering: Requirements and challenges. Chinese Journal of Computers, 2012,35(8):1-16 (in Chinese with English abstract). [CrossRef] [Google Scholar]
  23. Olivier Pivert, Etienne Scholly, Grégory Smits, Virginie Thion, Fuzzy quality-Aware queries to graph databases,Information Sciences,Volume 521,2020,Pages 160173,ISSN 0020-0255,\url{}. [Google Scholar]
  24. Chiang F, Miller RJ. A unified model for data and constraint repair. In: Proc. of the ICDE. Iscataway, NJ: IEEE Computer Society, 2011. [doi: 10.1109/ICDE.2011.5767833]. [Google Scholar]
  25. Liu BZ, Wang X, Liu PK, Li SZ, Zhang XW, Yang YJ. KGDB: Knowledge graph database system with unified model and query language. Ruan Jian Xue Bao/Journal of Software, 2021,32(3):781?804 (in Chinese). [Google Scholar]
  26. Zhong Ping, Li zhanhuai, Chen Qun. Functional dependency detection method in relational data [J]. Journal of computer science, 2017,40 (01): 207-222. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.