Abstract: The present disclosure relates to a method for a weighting graph comprising nodes representing entities and edges representing relationships between entities in accordance with one or more domains. The method comprises: pre-processing the graph comprising assigning weights to the nodes and/or the edges of the graph in accordance with a specific domain of the domains, wherein the weight indicates a domain specific data quality problem of attribute values representing an edge of the edges and/or an entity involved in that edge. The weighted graph may be provided for enabling a processing of the graph in accordance with the specific domain.

Abstract: A computer-implemented method for detecting a change in a meta-environment is disclosed. The method comprises collecting historic parameter values from at least one actor being active in the meta-environment, wherein each of the at least one actors has a set of abilities represented by parameters relating to the collected parameter values, collecting current parameter values from the at least one actor being active in the meta-environment, determining weight values of the collected historic parameters and weight values of the collected current parameters, and upon a value of a function of the determined weight values of the historic parameters and the weight values of the collected current parameters being greater than a predefined threshold value, determining a detection of the change in the meta-environment.

Abstract: Methods, computer program products and/or systems are provided that perform the following operations: obtaining a first graph comprising first nodes representing first entities and first edges representing relationships between first entities, the first nodes being associated with first entity attributes descriptive of the first entities represented by the first nodes, the first edges being associated with first edge attributes descriptive of the relationships represented by the first edges; determining a first subgraph for a certain node of the first nodes of the first graph, the first subgraph including the certain node and at least one neighboring node of the certain node; and determining a data quality issue regarding the certain node based, at least in part, on applying one or more applicable rules of a set of data quality rules to first entity attribute values and first edge attribute values of the first subgraph.

Abstract: In an approach, a processor receives a first record from a first data source, where the first record comprises attributes, a second record from a second data source, where the second record comprises said attributes, a first individual quality rating for the attributes of the first record, and a second individual quality rating for the attributes of the second record. A processor, in response to inputting the first record and the second record into a probabilistic matching engine, receives a matching score for each of the respective attributes. A processor calculates a weighted matching score for each of the respective attributes by weighting the matching score for each of the respective attributes with the first individual quality rating and the second individual quality rating. A processor assesses whether the first record and the second record represent the same entity based on the weighted matching score.

Abstract: Embodiments of the present invention determines duplicates in a graph. The graph comprises nodes representing entities and edges representing relationships between the entities. The method comprises: identifying at least two nodes in the graph. A neighborhood subgraph may be determined for each of the two nodes. The neighborhood subgraph includes the respective node. The method further comprises determining whether the two nodes are duplicates with respect to each other, based on a result of a comparison between the two subgraphs.

Abstract: Methods, computer program products and/or systems are provided that perform the following operations: obtaining a first graph comprising first nodes representing first entities and first edges representing relationships between first entities, the first nodes being associated with first entity attributes descriptive of the first entities represented by the first nodes, the first edges being associated with first edge attributes descriptive of the relationships represented by the first edges; determining a first subgraph for a certain node of the first nodes of the first graph, the first subgraph including the certain node and at least one neighboring node of the certain node; and determining a data quality issue regarding the certain node based, at least in part, on applying one or more applicable rules of a set of data quality rules to first entity attribute values and first edge attribute values of the first subgraph.

Abstract: The present disclosure relates to a method for a weighting graph comprising nodes representing entities and edges representing relationships between entities in accordance with one or more domains. The method comprises: pre-processing the graph comprising assigning weights to the nodes and/or the edges of the graph in accordance with a specific domain of the domains, wherein the weight indicates a domain specific data quality problem of attribute values representing an edge of the edges and/or an entity involved in that edge. The weighted graph may be provided for enabling a processing of the graph in accordance with the specific domain.

Abstract: Embodiments of the present invention determines duplicates in a graph. The graph comprises nodes representing entities and edges representing relationships between the entities. The method comprises: identifying at least two nodes in the graph. A neighborhood subgraph may be determined for each of the two nodes. The neighborhood subgraph includes the respective node. The method further comprises determining whether the two nodes are duplicates with respect to each other, based on a result of a comparison between the two subgraphs.