Ruoyu Wang

Orcid: 0000-0002-8278-3269

Affiliations:
  • Shanghai Jiao Tong University, School of Software, China


According to our database1, Ruoyu Wang authored at least 16 papers between 2016 and 2024.

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Bibliography

2024
Estimation-based optimizations for the semantic compression of RDF knowledge bases.
Inf. Process. Manag., 2024

2023
Symbolic Minimization on Relational Data.
IEEE Trans. Knowl. Data Eng., September, 2023

Horn rule discovery with batched caching and rule identifier for proficient compressor of knowledge data.
Softw. Pract. Exp., March, 2023

2022
SInC: Semantic approach and enhancement for relational data compression.
Knowl. Based Syst., 2022

RDF Knowledge Base Summarization by Inducing First-Order Horn Rules.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021
Essence of Factual Knowledge.
CoRR, 2021

2020
Pipeline provenance for cloud-based big data analytics.
Softw. Pract. Exp., 2020

Statistical Detection of Collective Data Fraud.
CoRR, 2020

Statistical Detection Of Collective Data Fraud.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2020

2019
Data Provenance Based System for Classification and Linear Regression in Distributed Machine Learning.
Proceedings of the Structured Object-Oriented Formal Language and Method, 2019

2018
A customised automata algorithm and toolkit for language learning and application.
Int. J. Big Data Intell., 2018

Comparison among Four Prominent Text Processing Tools.
Proceedings of the 15th International Symposium on Pervasive Systems, 2018

Intelligent Healthcare Knowledge Resources in Chinese: A Survey.
Proceedings of the 15th International Symposium on Pervasive Systems, 2018

2017
Efficient Density-Based Blocking for Record Matching.
Proceedings of the 21st International Database Engineering & Applications Symposium, 2017

2016
CAT: A Customized Automata Toolkit.
Proceedings of the 2016 IEEE International Conference on Software Quality, 2016

LogProv: Logging events as provenance of big data analytics pipelines with trustworthiness.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016


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