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US 2020/0050604 A1Published application
Approaches for knowledge graph pruning based on sampling and information gain theory
AssigneeAccenture Global Solutions Limited
InventorsTeresa Sheausan Tung, Colin Anil Puri, Zhijie Wang
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Abstract
Knowledge graph systems are disclosed for implementing multiple approaches, including stand alone or combined approaches, for knowledge graph pruning. The approaches are based on graph sampling work such as, for example, information gain theory. The approaches are applied by a knowledge graph system to perform schema pruning, automatic graph pruning, and query correlation for improving query performance.
Claims20
A knowledge graph system comprising:
- graph sampling circuitry configured to:
- receive a query request;
- analyze historical query patterns run on a knowledge graph for previously received query results that are similar to the query request;
- and
- select one or more candidate traversal paths included in the knowledge graph based on the analysis, wherein a candidate traversal path is comprised of at least one candidate entity node and at least one candidate edge connected to the at least one candidate entity node;
- schema pruning circuitry configured to:
- receive a candidate list including the one or more candidate traversal paths;
- analyze the historical query patterns;
- determine historical knowledge graph schema used on the knowledge graph based on the analysis;
- compare the historical knowledge graph schema with the candidate list;
- and
- remove candidate traversal paths from the knowledge graph based on the comparison.
9 more elements
A knowledge graph pruning method comprising:
- receiving, by graph sampling circuitry, a query request;
- analyzing, by the graph sampling circuitry, historical query patterns run on a knowledge graph for previously received query results that are similar to the query request;
- selecting, by the graph sampling circuitry, one or more candidate traversal paths included in the knowledge graph based on the analysis, wherein a candidate traversal path is comprised of at least one candidate entity node and at least one candidate edge connected to the at least one candidate entity node;
- receiving, by a schema pruning circuitry, a candidate list including the one or more candidate traversal paths;
- analyzing, by the schema pruning circuitry, the historical query patterns;
- determining, by the schema pruning circuitry, historical knowledge graph schema used on the knowledge graph based on the analysis;
- comparing, by the schema pruning circuitry, the historical knowledge graph schema with the candidate list;
- and
- removing, by the schema pruning circuitry, candidate traversal paths from the knowledge graph based on the comparison.
6 more elements
A computing device comprising:
- a non-transitory machine-readable medium;
- and
- instructions stored on the machine-readable medium, the instructions configured to, when executed by processing circuitry, cause the processing circuitry to:
- receive a query request;
- analyze historical query patterns run on a knowledge graph for previously received query results that are similar to the query request;
- select one or more candidate traversal paths included in the knowledge graph based on the analysis, wherein a candidate traversal path is comprised of at least one candidate entity node and at least one candidate edge connected to the at least one candidate entity node;
- receive a candidate list including the one or more candidate traversal paths;
- analyze the historical query patterns;
- determine historical knowledge graph schema used on the knowledge graph based on the analysis;
- compare the historical knowledge graph schema with the candidate list;
- and
- remove candidate traversal paths from the knowledge graph based on the comparison.
9 more elements
Dependencies are inferred from the claim text.