Intuit, Inc.

Anu Singh

Saikat Mukherjee

Karpaga Ganesh Patchirajan

Mritunjay Kumar

Yogish Pai

Steve George Goyette

Ling Feng Wei

Jay Jie-Bing Yu

Ram Mohan Shamanna

Peter Thomas

Madhusudhanan Dharumaraj

Joven Matias

A system for account mapping includes functionality for obtaining more than one labeled accounts labeled by more than one accountant; pre-processing more than one labeled accounts using natural language processing, using the more than one pre-processed labeled accounts to train an account mapping model that performs multinomial classification; receiving an account name from an accounting application where the account name includes a text label for an account included in a chart of accounts; generating an account mapping by applying the account mapping model to the account name, where the account mapping includes a type of the account, a sub-type of the account, a code, and a series associated with an accounting form; returning the account mapping to the accounting application through an Application Programming Interface (API); and receiving a corrected account mapping from an accountant and using the corrected account mapping as a new text label to incrementally update the account mapping model.

Automated field-mapping of account names for form population

A method may include acquiring, from an initial document having a document type, initial document elements and initial attributes, deriving initial features for the initial document elements using the initial attributes, detecting initial form components using the initial features, clustering the initial form components into initial line objects of an initial structured representation by applying an unsupervised machine learning model to the geometric attributes of the initial document elements, acquiring, from a next document having the document type, next document elements and next attributes describing the next document elements, deriving next features for the next document elements using the next attributes, detecting next form components using the next features, determining that the initial form components and the next form components are different, clustering the next form components into next line objects of a next structured representation, and replacing the initial structured representation with the next structured representation.

Generating structured representations of forms using machine learning

Generating a difference between a first and second plurality of lines of text in structured machine-readable format may include determining, by at least one processor, a line of the second plurality of lines that constitutes a best match for a line of the first plurality of lines. The line of the first plurality of lines and its respective best match may be associated with a similarity score. The at least one processor may compare the similarity score to a threshold value. In response to determining that the similarity score is greater than or equal to the threshold value, the at least one processor may compute, the textual difference between the line of the first plurality of lines and its best match. In response to computing the textual difference, the at least one processor may analyze the textual difference to identify a non-meaningful change. In response to identifying a non-meaningful change, the at least one processor may record the textual difference in a delta with a flag indicating the presence of the non-meaningful change.

System and method of generating deltas between documents

A method may include acquiring, from a document, document elements and attributes describing the document elements. One or more of the attributes may be geometric attributes describing a placement of the corresponding document element within the document. The method may further include deriving features for the document elements using the attributes, detecting form components using the features, clustering the form components into line objects of a structured representation by applying an unsupervised machine learning model to the geometric attributes of the document elements, and populating a compliance form using the structured representation.

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Anu Singh