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Normalizing property graphs
Normalization aims at minimizing sources of potential data inconsistency and costs of
update maintenance incurred by data redundancy. For relational databases, different …
update maintenance incurred by data redundancy. For relational databases, different …
Transforming property graphs
A Bonifati, F Murlak, Y Ramusat - ar** Functional Dependencies to the Future Property Graph Schema Standard
There has been a notable effort, in the past five years, to develop and promote Graph Query
Language, GQL, as a standard for querying graph data, akin to the role SQL plays in …
Language, GQL, as a standard for querying graph data, akin to the role SQL plays in …
[PDF][PDF] ProGGD-Data Profiling on Knowledge Graphs using Graph Generating Dependencies.
Data profiling is usually performed in the very first step of a data analysis pipeline. The main
goal of data profiling is to present a comprehensive overview of the data contents and its …
goal of data profiling is to present a comprehensive overview of the data contents and its …
Large-scale data integration using graph probabilistic dependencies (gpds)
The diversity and proliferation of Knowledge bases have made data integration one of the
key challenges in the data science domain. The imperfect representations of entities …
key challenges in the data science domain. The imperfect representations of entities …
[PDF][PDF] Graph Profiling with Graph Generating Dependencies.
LC Shimomura - PhD@ VLDB, 2022 - ceur-ws.org
Data dependencies have a direct application to data profiling as they can provide
information about the metadata. The rise of practical real-world use of graph data resulted in …
information about the metadata. The rise of practical real-world use of graph data resulted in …
[PDF][PDF] Generative AI for Graph Data Repair
A Bonifati, A Mauri - liris.cnrs.fr
Objectives The objective of this project is to study how generative AI, especially Generative
Adversarial Neural Networks and Large Language Models, can be used to data repair rules …
Adversarial Neural Networks and Large Language Models, can be used to data repair rules …