Knowledge Graph ↔ data cleaning

Relations (1)

related 0.30 — supporting 3 facts

Data cleaning is an essential process in the construction and maintenance of a Knowledge Graph, as it is used to transform raw input data into structured formats [1] and to identify erroneous or contradictory information within the graph [2] [3].

Facts (3)

Sources

Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org arXiv 3 facts

claimData cleaning approaches used in Knowledge Graph construction can be applied to the final Knowledge Graph to identify outliers or contradicting information.

procedureExtraction methods for semi-structured data typically combine data cleaning and rule-based mappings to transform input data into a knowledge graph, targeting defined classes and relations of an existing ontology.

claimData profiling and cleaning techniques can be applied to identify erroneous values in a knowledge graph based on their distribution.