KNOWLEDGE GRAPH IMPLEMENTATION

1 . A computer system for implementing a dynamic compliance knowledge graph comprising:

one or more processors; and

one or more computer-readable media having stored thereon executable instructions that when executed by the one or more processors configure the computer system to:

receive a digital file including a compliance file, which includes one or more levels of compliance processes in a hierarchical order;

generate a knowledge graph from text within the digital file by:

creating nodes based on one or more text entities within the digital file;

creating edges based on relationships between the nodes within the digital file, and

generating the knowledge graph based on the nodes and the edges;

receive a query regarding compliance to the digital file;

calculate a metric between each node to a query vector of the query; and

provide one or more compliance paths to one or more target nodes based on metrics.

2 . The computer system according to claim 1 , wherein each node of the knowledge graph includes metadata, which identifies every hierarchical level to which each node belongs.

3 . The computer system according to claim 1 , wherein each node of the knowledge graph includes text information of a corresponding portion of the digital file.

4 . The computer system according to claim 1 , wherein each node is represented as a vector, and

any two nodes may be compared with each other to calculate the metric therebetween.

5 . The computer system according to claim 1 , wherein the instructions, when executed by the one or more processors, further configure the computer system to:

embed the query into the query vector, wherein

the query vector is compared to a vector of each node to calculate a respective metric therebetween.

6 . The computer system according to claim 1 , wherein providing the one or more compliance paths includes finding a first target node based on highest semantic similarity.

7 . The computer system according to claim 6 , wherein the one or more compliance paths share a majority of a compliance path to the first target node.

8 . The computer system according to claim 7 , wherein a metric between each of the one or more target nodes and the one or more compliance paths is less than a threshold.

9 . The computer system according to claim 1 , wherein the digital file includes a regulation file including one or more levels of regulations in a hierarchical order.

10 . The computer system according to claim 9 , wherein a portion of nodes of the knowledge graph related to the compliance file is connected to a portion of nodes of a knowledge graph related to the regulation file via edges.

11 . A method for implementing a compliance knowledge graph, the method comprising:

receiving a digital file including a compliance file, which includes one or more levels of compliance processes in a hierarchical order;

generating a knowledge graph from text within the digital file by:

creating nodes based on one or more text entities within the digital file;

creating edges based on relationships between the nodes within the digital file; and

generating the knowledge graph based on the nodes and the edges;

receiving a query regarding compliance to the digital file;

calculating a metric between each node to a query vector of the query; and

providing one or more compliance paths to one or more target nodes based on metrics.

12 . The method according to claim 11 , wherein each node of the knowledge graph includes metadata, which identifies every hierarchical level to which each node belongs.

13 . The method according to claim 11 , wherein each node of the knowledge graph includes text information of a corresponding portion of the digital file.

14 . The method according to claim 11 , further comprising:

embedding the query into the query vector, wherein

the query vector is compared to a vector of each node to calculate a respective metric therebetween.

15 . The method according to claim 11 , wherein providing the one or more compliance paths includes finding a first target node based on highest semantic similarity.

16 . The method according to claim 15 , wherein the one or more compliance paths share a majority of a compliance path to the first target node.

17 . The method according to claim 16 , wherein a metric between each of the one or more target nodes and the one or more compliance paths is less than a threshold.

18 . The method according to claim 11 , wherein the digital file includes a regulation file including one or more levels of regulations in a hierarchical order.

19 . The method according to claim 18 , wherein a portion of nodes of the knowledge graph related to the compliance file is connected to a portion of nodes of a knowledge graph related to the regulation file via edges.

20 . A nontransitory computer readable medium including computer executable instructions that, when executed by a computer, cause the computer to perform a method for implementing a compliance knowledge graph, the method comprising:

receiving a digital file including a compliance file, which includes one or more levels of compliance processes in a hierarchical order;

generating a knowledge graph from text within the digital file by:

creating nodes based on one or more text entities within the digital file;

creating edges based on relationships between the nodes within the digital file; and

generating the knowledge graph based on the nodes and the edges;

receiving a query regarding compliance to the digital file;

calculating a metric between each node to a query vector of the query; and

providing one or more compliance paths to one or more target nodes based on metrics.