Patents by Inventor Allan Barcelos
Allan Barcelos has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11900328Abstract: A method, computer system, and computer program product are provided for managing reports. A subset of data fields is identified for inclusion in a new report. An intent of the new report is determined based on the subset of data fields. The intent is determined using a set of machine learning models trained from a set of existing reports and a taxonomy of human capital management (HCM) information. Based on the intent determined by the artificial intelligence system, a set of additional fields is predicted for the new report. The set of the additional fields is displayed in a graphical user interface on a display system.Type: GrantFiled: December 1, 2020Date of Patent: February 13, 2024Assignee: ADP, Inc.Inventor: Allan Barcelos
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Publication number: 20240037003Abstract: A method of sparse intent clustering is provided. The method comprises identifying features in a number of electronic user reports created by a user and contained in a database, wherein the features include a title and description. The features of each user report are encoded into a binary vector. The binary vector for each user report is fed into an autoencoder neural network that creates a N-dimensional vector representing the user report. The float vectors representing the user reports are projected into a N-dimensional space. The float vectors are clustered according to cosine similarities, wherein each vector cluster represents an intent of the user in creating the reports. The intent of each vector cluster is then labeled.Type: ApplicationFiled: October 2, 2023Publication date: February 1, 2024Applicant: ADP, Inc.Inventors: Allan Barcelos, Fernanda Tosca, Israel Oliveira, Leandro Bianchini, Renata Palazzo
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Patent number: 11775408Abstract: A method of sparse intent clustering is provided. The method comprises identifying features in a number of electronic user reports created by a user and contained in a database, wherein the features include a title and description. The features of each user report are encoded into a binary vector. The binary vector for each user report is fed into an autoencoder neural network that creates a N-dimensional vector representing the user report. The float vectors representing the user reports are projected into a N-dimensional space. The float vectors are clustered according to cosine similarities, wherein each vector cluster represents an intent of the user in creating the reports. The intent of each vector cluster is then labeled.Type: GrantFiled: August 3, 2020Date of Patent: October 3, 2023Assignee: ADP, INC.Inventors: Allan Barcelos, Fernanda Tosca, Israel Oliveira, Leandro Bianchini, Renata Palazzo
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Publication number: 20230297598Abstract: A method of latent intent clustering is provided. The method comprises encoding identified features in a number of electronic user reports in a database. A binary matrix is created, wherein each row of the binary matric represents a different report and each column represents a different available feature. A 1 is placed in each cell of the matrix that matches a feature present in a user report. Cosine similarities are calculated for the user reports, and a similarity matrix is created, wherein each row and column of the binary matrix represents a different report, and wherein the cosine similarities of the reports are placed in corresponding cells of the matrix. The reports are clustered according to the cosine similarities. Features common to reports in each cluster are identified, and an intent of each report cluster is labeled according to the common features.Type: ApplicationFiled: March 23, 2023Publication date: September 21, 2023Applicant: ADP, Inc.Inventors: Leandro Bianchini, Renata Palazzo, Israel Oliveira, Allan Barcelos, Fernanda Tosca
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Publication number: 20230281188Abstract: A method, computer system, and computer program product are provided for generating reports. Existing reports are collected and modeled to determine a number of contexts. An index of the existing reports is generated according the contexts determined by the modeling. a predicted context of a new report is predicted according to the modeling. According to the index, suggested reports are identified based on the predicted context for the new report. The suggested reports are presented in a graphical user interface.Type: ApplicationFiled: February 16, 2023Publication date: September 7, 2023Applicant: ADP, INC.Inventors: Israel Oliveira, Allan Barcelos, Renata Palazzo, Leandro Bianchini, Fernanda Tosca
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Publication number: 20220172174Abstract: A method, computer system, and computer program product are provided for managing reports. A subset of data fields is identified for inclusion in a new report. An intent of the new report is determined based on the subset of data fields. The intent is determined using a set of machine learning models trained from a set of existing reports and a taxonomy of human capital management (HCM) information. Based on the intent determined by the artificial intelligence system, a set of additional fields is predicted for the new report. The set of the additional fields is displayed in a graphical user interface on a display system.Type: ApplicationFiled: December 1, 2020Publication date: June 2, 2022Inventor: Allan Barcelos
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Publication number: 20220122010Abstract: A method, computer system, and computer program product are provided for generating reports. A subset of data fields is identified for inclusion in a new report. A context of the new report is determined based on the subset and a sequence in which the data fields of the subset were identified. Using a machine learning model, a set of suggested fields is determined based on the context of the new report. The set of the suggested fields in a graphical user interface on a display system.Type: ApplicationFiled: October 15, 2020Publication date: April 21, 2022Inventors: Allan Barcelos, Leandro Bianchini, Fernanda Tosca
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Publication number: 20220083568Abstract: A method of latent intent clustering is provided. The method comprises encoding identified features in a number of electronic user reports in a database. A binary matrix is created, wherein each row of the binary matric represents a different report and each column represents a different available feature. A 1 is placed in each cell of the matrix that matches a feature present in a user report. Cosine similarities are calculated for the user reports, and a similarity matrix is created, wherein each row and column of the binary matrix represents a different report, and wherein the cosine similarities of the reports are placed in corresponding cells of the matrix. The reports are clustered according to the cosine similarities. Features common to reports in each cluster are identified, and an intent of each report cluster is labeled according to the common features.Type: ApplicationFiled: September 15, 2020Publication date: March 17, 2022Inventors: Leandro Bianchini, Renata Palazzo, Israel Oliveira, Allan Barcelos, Fernanda Tosca
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Publication number: 20220035722Abstract: A method of sparse intent clustering is provided. The method comprises identifying features in a number of electronic user reports created by a user and contained in a database, wherein the features include a title and description. The features of each user report are encoded into a binary vector. The binary vector for each user report is fed into an autoencoder neural network that creates a N-dimensional vector representing the user report. The float vectors representing the user reports are projected into a N-dimensional space. The float vectors are clustered according to cosine similarities, wherein each vector cluster represents an intent of the user in creating the reports. The intent of each vector cluster is then labeled.Type: ApplicationFiled: August 3, 2020Publication date: February 3, 2022Inventors: Allan Barcelos, Fernanda Tosca, Israel Oliveira, Leandro Bianchini, Renata Palazzo
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Publication number: 20220035795Abstract: A method, computer system, and computer program product are provided for generating reports. Existing reports are collected and modeled to determine a number of contexts. An index of the existing reports is generated according the contexts determined by the modeling. a predicted context of a new report is predicted according to the modeling. According to the index, suggested reports are identified based on the predicted context for the new report. The suggested reports are presented in a graphical user interface.Type: ApplicationFiled: August 3, 2020Publication date: February 3, 2022Inventors: Israel Oliveira, Allan Barcelos, Renata Palazzo, Leandro Bianchini, Fernanda Tosca