Abstract: A data processing method includes receiving data from a plurality of sources, generating a knowledge graph, and identifying potentially ambiguous particular nodes. For each of the particular nodes a semantic neighborhood is constructed including the particular node and a plurality of nodes within a particular degree of separation from the particular node, the particular node is omitted from the semantic neighborhood, a plurality of groups of connected nodes are determined in the semantic neighborhood, a plurality of instances of the particular node are defined, a plurality of substitute nodes are generated based on the plurality of instances, and each of the plurality of groups of connected nodes are connected to one of the plurality of substitute nodes to update the knowledge graph. A query is received via a network. Query results are retrieved out of the updated knowledge graph, and the query results are rendered accessible.

Abstract: A method includes accessing a database including a table including a first column including a first plurality of values, a second column including a second plurality of values, and a plurality of rows. A knowledge graph is constructed including a first plurality of nodes based on the first plurality of values, a second plurality of nodes based on the second plurality of values, and a plurality of node connections. A missing value is detected in the second column. A first particular value of the first plurality of values is detected in the first column. A first particular node corresponding to the first particular value is detected. The first particular node is determined to be connected to a second particular node corresponding to a second particular value of the second plurality of values, and the missing value is filled with the second particular value.

Abstract: A data processing method includes receiving data from a plurality of sources, generating a knowledge graph, and identifying potentially ambiguous particular nodes. For each of the particular nodes a semantic neighborhood is constructed including the particular node and a plurality of nodes within a particular degree of separation from the particular node, the particular node is omitted from the semantic neighborhood, a plurality of groups of connected nodes are determined in the semantic neighborhood, a plurality of instances of the particular node are defined, a plurality of substitute nodes are generated based on the plurality of instances, and each of the plurality of groups of connected nodes are connected to one of the plurality of substitute nodes to update the knowledge graph. A query is received via a network. Query results are retrieved out of the updated knowledge graph, and the query results are rendered accessible.

Abstract: A computer method for resolving entity identity. The method includes recording a plurality of entities by denoting a plurality of attributes about the plurality of entities via a plurality of labels comprising a plurality of data sets. A plurality of connection conditions between the plurality of data sets are determined, the plurality of connection conditions comprising a plurality of weight conditions. The plurality of weight conditions are reduced based on a probability function. The plurality of data sets are separated into a plurality of data subsets based on the plurality of weight conditions of the plurality of connection conditions to identify particular attributes of the plurality of data subsets, and the particular attributes of the plurality of subsets are transmitted.

Abstract: A method for resolving entities in a knowledge graph including determining node sets in the knowledge graph, determining each of the node sets includes determining a first node, determining a second node in a semantic neighborhood of the first node, and determining a third node in the semantic neighborhood of the first node. For each node set, the second node and the third node are compared, and it is determined that the second node and the third node are a similar node pair. For each similar node pair, the first nodes of the node sets are aggregated, and a quantity of overlapping of a semantic neighborhood of the second node and a semantic neighborhood of the third node is determined, and for each similar node pair, the second and third nodes are resolved as a single entity.

Abstract: A computer method for resolving entity identity. The method includes recording a plurality of entities by denoting a plurality of attributes about the plurality of entities via a plurality of labels comprising a plurality of data sets. A plurality of connection conditions between the plurality of data sets are determined, the plurality of connection conditions comprising a plurality of weight conditions. The plurality of weight conditions are reduced based on a probability function. The plurality of data sets are separated into a plurality of data subsets based on the plurality of weight conditions of the plurality of connection conditions to identify particular attributes of the plurality of data subsets, and the particular attributes of the plurality of subsets are transmitted.