Intuit, Inc.

Optum, Inc.

Cem Unsal

Saikat Mukherjee

Roger Charles Meike

Anu Sreepathy

Per-Kristian G Halvorsen

William Taylor Laaser

David Alan Hanekamp, Jr

Michael A Artamonov

Mritunjay Kumar

Gang Wang

Calum G Murray

Todd Elliott

Steven J Atkinson

Ramin Anushiravani

Jason Hardiman

Saneesh Joseph

Yizhao Ni

Harsh M Maheshwari

Micah David Ketola

Per-Kristian Halvorsen

William T Laaser

Various embodiments of the present disclosure provide model-based domain-aware autocomplete techniques for generating autocomplete suggestions in a complex search domain. Example embodiments are configured to generate, using a domain-aware autocomplete model, a label for an autocomplete suggestion based on a set of keywords within an autocomplete suggestion training dataset associated with a target domain source. Example embodiments are also configured to generate, using a weak-labeling model, an updated label for the autocomplete suggestion by decorrelating the set of keywords from the label. Example embodiments are also configured to generate, using a sentence classification model, a category for the autocomplete suggestion based on the updated label. Example embodiments are also configured to, using the domain-aware autocomplete model, generate a suggestion-category pair (SCP) based on the autocomplete suggestion and the category for the autocomplete suggestion. Example embodiments are also configured for initiating performance of a search query resolution based on the SCP.

Domain-aware autocomplete

A method and system learn functions to be associated with data fields of forms to be incorporated into an electronic document preparation system. The functions are essentially sets of operations required to calculate the data field. The method and system receive form data related to a data field that expects data values resulting from performing specific operations. The method and system utilize machine learning and training set data to generate, test, and evaluate candidate functions to determine acceptable functions.

System and method for automatic learning of functions

A method and system to learn new forms to be incorporated into an electronic document preparation system, or to learn the behavior of existing systems, receive form data related to a new form having a plurality of data fields that expect data values based on specific functions. The method and system gather training set data including previously filled forms having completed data fields corresponding to the data fields of the new form. The method and system include multiple analysis modules that each generate candidate functions for providing data values for the data fields of the new form. The method and system evaluate the candidate functions from each analysis technique and select the candidate functions that are most accurate based on comparisons with the training set data.

System and method for automatically generating calculations for fields in compliance forms

A method and system learns functions to be associated with data fields of forms to be incorporated into an electronic document preparation system. The functions are essentially sets of operations required to calculate the data field. The method and system receive form data related to a data field that expects data values resulting from performing specific operations. The method and system utilize machine learning and training set data to generate, test, and evaluate candidate functions to determine acceptable functions.

A method and system generate sample data set for efficiently and accurately testing a new calculation for preparing a portion of an electronic document for users of an electronic document preparation system. The method and system receive the new calculation and gather historical use data related to previously prepared electronic documents for a large number of historical users. The method and system group the historical users into groups based on which sections of a previous version of electronic document preparation software were executed for each historical user in preparing electronic documents for the historical users. The groups are then sampled by selecting a small number of historical users from each group.

System and method for identifying a subset of total historical users of a document preparation system to represent a full set of test scenarios based on code coverage

A method and system generates sufficient sample data sets for efficiently and accurately testing a new calculation for preparing a portion of an electronic document for users of an electronic document preparation system. The method and system prepares the new calculation and gathers historical user data related to previously prepared electronic documents for a large number of historical users. The method and system generates a representative value for each historical user data, based on the sections of a previous version of electronic document preparation software which were executed for each historical user in preparing electronic documents for the historical users. The method and system groups the historical users based on the hash values which indicates the historical user's behavior in the software. The groups are then sampled by selecting a small number of historical users from each group.

System and method for identifying a subset of total historical users of a data management system to represent a full set of test scenarios based on prehashing of code coverage information

A method for collecting a payment. The method includes sending, to a payor, a request for the payment, wherein the request comprises an original payment amount and an original payment due date, generating, based on a set of payment collection records from an online financial management application used by payees, a payment statistical measure representing a payment behavior of payors paying the payees, generating, based on the payment statistical measure, the original payment amount, and the original payment due date, an adjusted payment amount and a condition to qualify the adjusted payment amount for completing the payment, enabling, prior to the payor completing the payment, the payor to view the adjusted payment amount and the condition, wherein the payor completes the payment in response to at least the payor viewing the adjusted payment amount and the condition, and collecting the payment completed by the payor.

Gamification of fields in online e-commerce documents

A method and system learns new forms to be incorporated into an electronic document preparation system. The method and system receive form data related to a new form having a plurality of data fields that expect data values based on specific functions. The method and system gather training set data including previously filled forms having completed data fields corresponding to the data fields of the new form. The method and system group the training set data into groups and sample the groups. The method and system utilize machine learning in conjunction with the sampled training set data to identify an acceptable function for each of the data fields of the new form. The grouped and sampled training set data can also be passed to a quality assurance system.

System and method for selecting data sample groups for machine learning of context of data fields for various document types and/or for test data generation for quality assurance systems

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Alameda, CA, United States of America

Cem Unsal