Adp, Inc.

Automatic Data Processing, Inc.

Guilherme Gomes

Roberto Pereira Silveira

Roberto Coutinho

Roberto Rodrigues Dias

Jarismar Silva

Bruno Apel

Carlos Nascimento

Vincent Kellers

Roberto A Masiero

Stefan Zanona

Wagner Peres

Leonardo Santos

Roberto Masiero

Mallie Griffin

Anjo Costa

Roberto Silveira

Systems, methods, and computer-readable storage media for responding to a query using a neural network and natural language processing. If necessary, the system can request disambiguation, then parse the query using a trained machine-learning classifier, resulting in at least one of an identified subject or an identified domain of the text query. The system can determine if the user is authorized to retrieve answers to the query and, if so, retrieve factual data associated with the query. The system can then retrieve a response template, and fill in the template with the retrieved facts. The system can then determine, by executing a machine comprehension model on the filled response template, a probable readability token, portion of text, of at least a portion of the filled response template and, upon identifying that the probable readability is above a threshold, reply to the text query with the at least a portion of the filled response template.

System and method for query authorization and response generation using machine learning

Systems, methods, and computer-readable storage media for recommending computational commands based on a weighted, ranked hierarchical graph. The system converts a map of intended user actions to canonical actions (commands) into a graph representation. Then, via a chatbot algorithm, the system receives an initial intent as a request by a user of the chatbot algorithm. Based on the popularity of alternative canonical actions, the system makes recommendations of alternative actions which are similar to the initial intent provided by the user.

System and method for recommending computational commands based on a weighted, ranked hierarchical graph

A method receives an electronic image and uses the image as an input to a neural network. Based on a determination that the image represents a document, the method uses the image as an input to another neural network to identify a portion of the document containing an identifier. The method extracts the identifier by performing character recognition on the identified portion and determines whether the identifier is valid by using a validation API to determine whether the identifier is associated with a valid account at an institution. Based on a determination that the identifier is associated with a valid account, the method authorizes a transaction associated with the identifier. Based on a determination that the identifier is not associated with a valid account, the method denies the transaction. The first neural network classifies the electronic image into one of multiple valid document types and an invalid document type.

Multi-model system for electronic transaction authorization and fraud detection

Method to recommend intents based on a weighted ranked hierarchical graph

Systems, methods, and computer-readable storage media for identifying and generating insights using machine learning and serverless computing systems. When events are detected, data from those events is collected and formatted into predefined formats. That formatted data is then used within an instance, where a machine learning algorithm is executed by a serverless computing system using the data within the instance as input. The result from the machine learning algorithm is an insight into the event and event data, which can be presented to users for interpretation.

System and method for serverless modification and execution of machine learning algorithms

Aspects extract, from payroll data of employees of an organization, data historically associated to previous instances of certified tax credit eligibility; normalize the extracted data with respect to data type and data value; generate from the normalized extracted data via a neural network classifier multi-class outputs for each employee that indicate strengths of likelihood that each employee is currently eligible for each of a plurality of different tax credits; filter the normalized extracted data by removing portions associated to employees indicated within the multi-class outputs as having no currently eligible likelihood for the different tax credits, thereby generating a remainder set of normalized extracted data associated to remainder eligible ones of the employees; and prioritize application for the tax credits for the remainder eligible employees as a function of respective values and likelihoods of eligibility within the remainder set of normalized extracted data.

Credit eligibility predictor

A method, computer system, and computer program product are provided for managing time record events. Time record events are collected for a number of users. Each time record event includes a geolocation of one of a number of users. The time record events and geolocations for each of the number of users are models via machine learning. A current geolocation for a given user is identified. A suggested event is predicted based on the current geolocation and a current time. The suggested event is pushed to the user.

Multi-task deep learning of time record events

Growing community of inventors

Porto Alegre, Brazil

Guilherme Gomes