Identifying redundant nodes in a knowledge graph data structure

A computer system for eliminating a redundant node from a knowledge graph, the computer system comprising:

• one or more computer processors;
• one or more computer-readable storage media;
• program instructions stored on the computer processor for execution by at least one of the one or more processors, the program instructions comprising:
• program instructions to perform a structural analysis of a knowledge graph by determining that two nodes have a similar structure, the similar structure of the two nodes indicated similarity of one or more of the following structural elements:
• a linkage pattern, a graph centrality, or a graph isomorphism;
• program instructions to perform an empirical analysis by determining a search result correlation of potentially redundant nodes having the similar structure independent of a context of the potentially redundant nodes, said search result correlation comprising a correlation of search result nodes generated from different search queries to said knowledge graph or a correlation of search results due to search results due to selected search result nodes in subtrees of said potentially redundant nodes;
• program instructions to combine results of said structural analysis and said empirical analysis to generate a redundancy confidence level value for said two nodes;
• program instructions to determine one of said two nodes as redundant if said redundancy confidence level value exceeds a confidence level threshold;
• and
• program instructions to remove the node determined to be redundant from the knowledge graph.

A computer program product using a computing device to eliminate a redundant node from a knowledge graph, the computer program product comprising:

• one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions, when executed by the computing device, cause the computing device to perform a method comprising:
• performing a structural analysis of a knowledge graph by determining that two nodes have a similar structure, the similar structure of the two nodes indicated by similarity of one or more of the following structural elements:
• linkage pattern, a graph centrality, or a graph isomorphism;
• performing an empirical analysis, by determining a search result correlation of potentially redundant nodes having the similar structure independent of a context of the potentially redundant nodes, said search result correlation comprising a correlation of search result nodes generated from different search queries to said knowledge graph or a correlation of search results due to selected search result nodes in subtrees of said potentially redundant nodes;
• combining results of said structural analysis and said empirical analysis to generate a redundancy confidence level value for said two nodes;
• determining one of said two nodes as redundant if said redundancy confidence level value exceeds a confidence level threshold;
• and
• removing the node determined to be redundant from the knowledge graph.