Computing application for determining data associated with a computing record using a probabilistic model

1 . A method for determining data associated with at least one computing record using a probabilistic computing operation, the method comprising:

receiving, using one or more computing device processors, from a first user, at least one computing record;

determining, using the one or more computing device processors, image data associated with the at least one computing record;

generating, using the one or more computing device processors, structural data, wherein the structural data comprises one or more hierarchical relationships based on the image data associated with the at least one computing record;

generating, using the one or more computing device processors, dimensional data, wherein the dimensional data comprises one or more spatial relationships based on the image data associated with the at least one computing record;

determining, using the one or more computing device processors, based on the structural data comprising the one or more hierarchical relationships based on the image data associated with the at least one computing record and the dimensional data comprising the one or more spatial relationships based on the image data associated with the at least one computing record, a relational graph, wherein the relational graph defines relationships associated with the at least one computing record;

receiving, using the one or more computing device processors, from the first user, a first rule associated with processing the at least one computing record;

parsing, using the one or more computing device processors, the first rule, thereby generating a first parsed rule;

generating, using the one or more computing device processors, based on the first parsed rule, an abstract syntax tree;

first analyzing, using the one or more computing device processors, based on a first computing record comprised in the at least one computing record, the abstract syntax tree;

generating, using the one or more computing device processors, based on the first analyzing the abstract syntax tree, a first rule result associated with the first rule;

applying, using the one or more computing device processors, the first rule to a probabilistic computing operation, wherein the applying the first rule to the probabilistic computing operation comprises:

second analyzing, based on the at least one computing record, the abstract syntax tree, and

generating, based on the second analyzing the abstract syntax tree, at least one first rule result associated with the first rule;

determining, using the one or more computing device processors, based on the applying the first rule result to the probabilistic computing operation, a first indicator associated with the first rule result and the at least one first rule result;

determining, using the one or more computing device processors, based on the first indicator associated with the first rule result and the at least one first rule result, whether the probabilistic computing operation requires an update; and

upon determining the probabilistic computing operation requires the update, updating, using the one or more computing device processors, the probabilistic computing operation.

2 . The method of claim 1 , wherein the determining the image data comprises performing an optical character recognition (OCR) operation on the at least one computing record.

3 . The method of claim 1 , wherein the determining the image data comprises adapting to spatial noise introduced by an optical character recognition (OCR) operation on the at least one computing record.

4 . The method of claim 1 , wherein the first indicator associated with the first rule result and the at least one first rule result comprises an approximate accuracy or a score or a coverage value associated with the at least one computing record.

5 . The method of claim 1 , wherein the determining the relational graph comprises adapting to spatial noise.

6 . The method of claim 1 , wherein the first rule associated with processing the at least one computing record comprises an existing rule or a rule under development.

7 . The method of claim 6 , wherein the first rule is associated with a domain specific language.

8 . The method of claim 1 , wherein the parsing the first rule comprises utilizing a recurrent neural network.

9 . The method of claim 1 , wherein the applying the first rule to the probabilistic computing operation comprises utilizing a Naive Bayesian methodology to assess the first rule result.

10 . The method of claim 1 , wherein the applying the first rule to the probabilistic computing operation comprises allowing the probabilistic computing operation to determine, based on a history of rule results, a selection of the first rule or a first existing rule comprised in at least one existing rule to be applied to a second computing record.

11 . The method of claim 1 , wherein the determining whether the probabilistic computing operation requires the update comprises identifying a second computing record comprised in the at least one computing record that, upon applying the first rule, does not return a correct result.

12 . The method of claim 1 , wherein the determining whether the probabilistic computing operation requires the update comprises determining whether the probabilistic computing operation comprises a first shape.

13 . The method of claim 1 , wherein the updating the probabilistic computing operation comprises:

receiving, using the one or more computing device processors, from the first user, a second rule associated with processing the at least one computing record;

parsing, using the one or more computing device processors, the second rule, thereby generating a second parsed rule;

updating, using the one or more computing device processors, based on the second parsed rule, the abstract syntax tree;

third analyzing, using the one or more computing device processors, based on a second computing record comprised in the at least one computing record, the abstract syntax tree;

generating, using the one or more computing device processors, based on the third analyzing the abstract syntax tree, a second rule result associated with the second rule; and

applying, using the one or more computing device processors, the second rule result to the probabilistic computing operation.

14 . The method of claim 1 , wherein the probabilistic computing operation accounts for variance among the at least one computing record.

15 . The method of claim 14 , wherein the variance comprises at least one of: spatial variance or linguistic variance.

16 . The method of claim 14 , wherein the updating the probabilistic computing operation is based on or associated with the variance among the at least one computing record.

17 . The method of claim 1 , further comprising:

determining, using the one or more computing device processors, at least one of: an additional record added by the first user, or an additional rule added by the first user;

upon determining the first user added the additional record, updating, using the one or more computing device processors, based on the additional record, the relational graph, thereby generating an updated relational graph;

upon determining the first user added the additional rule, updating, using the one or more computing device processors, based on the additional rule, the abstract syntax tree, thereby generating an updated abstract syntax tree;

applying, using the one or more computing device processors, the additional rule to the probabilistic computing operation, wherein the applying the additional rule to the probabilistic computing operation comprises:

analyzing, based on the at least one computing record, the updated abstract syntax tree, and

generating, based on the analyzing the updated abstract syntax tree, at least one second rule result associated with the additional rule;

updating, using the one or more computing device processors, based on the applying the additional rule to the probabilistic computing operation, the first indicator associated with the first rule result and the at least one first rule result, thereby generating an updated first indicator; and

determining, using the one or more computing device processors, a second indicator associated with the at least one second rule result associated with the additional rule.

18 . A system for determining data associated with at least one computing record using a probabilistic computing operation, the system comprising:

one or more computing device processors; and

one or more computing device memories, coupled to the one or more computing device processors, the one or more computing device memories storing instructions executed by the one or more computing device processors, wherein the instructions are configured to:

receive, from a first user, at least one computing record;

determine image data associated with the at least one computing record;

generate structural data, wherein the structural data comprises one or more hierarchical relationships based on the image data associated with the at least one computing record;

generate dimensional data, wherein the dimensional data comprises one or more spatial relationships based on the image data associated with the at least one computing record;

determine, based on the structural data comprising the one or more hierarchical relationships based on the image data associated with the at least one computing record and the dimensional data comprising the one or more spatial relationships based on the image data associated with the at least one computing record, a relational graph, wherein the relational graph defines relationships associated with the at least one computing record;

receive, from the first user, a first rule associated with processing the at least one computing record;

parse the first rule, thereby generating a first parsed rule;

generate, based on the first parsed rule, a syntax tree;

first analyze, based on a first computing record comprised in the at least one computing record, the syntax tree;

generate, based on the first analyze the syntax tree, a first rule result associated with the first rule;

apply the first rule to a probabilistic computing operation, wherein the apply the first rule to the probabilistic computing operation comprises:

second analyzing, based on the at least one computing record, the syntax tree, and

generating, based on the second analyzing the syntax tree, at least one rule result associated with the first rule;

determine, based on the applying the first rule result to the probabilistic computing operation, an indicator associated with the first rule result and the at least one rule result;

determine, based on the indicator associated with the first rule result and the at least one rule result, whether the probabilistic computing operation requires an update; and

upon determining the probabilistic computing operation requires the update, update the probabilistic computing operation.

19 . The system of claim 18 , wherein the instructions are further configured to provide a user interface for displaying rules that have been executed.

20 . The system of claim 18 , wherein the instructions are further configured to provide a user interface for displaying details associated with at least one of the at least one computing record.

21 . The system of claim 18 , wherein the instructions are further configured to provide a user interface for allowing the first user to input at least one of the at least one computing record and the first rule.

22 . The system of claim 18 , wherein the instructions are further configured to provide a user interface for displaying details associated with at least one rule that is being developed.

23 . The system of claim 18 , wherein the instructions are further configured to provide a user interface for displaying details associated with the indicator associated with the first rule result.