Patents by Inventor Jacob Nathaniel Huffman
Jacob Nathaniel Huffman 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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Publication number: 20230089596Abstract: Database systems and methods are provided for assigning structural metadata to records and creating automations using the structural metadata.Type: ApplicationFiled: September 19, 2022Publication date: March 23, 2023Applicant: Salesforce, Inc.Inventors: Jacob Nathaniel Huffman, Zachary Alexander, Yixin Mao, Nicholas Feinig, Avanthika Ramesh, Zineb Laraki
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Patent number: 11580179Abstract: A method and system for recommending articles including: receiving a customer request from the customer during the session; generating case data for a case, by an article recommender app; configuring a training set based on the subject and description data of the customer request; identifying, by an artificial intelligence (AI) app, a first pool of articles from a knowledge database; identifying by at least one query, a second pool of articles from a case article database to into a merged pool of articles; assigning, by the AI app, an implicit label to one of the first pool and the second pool of the articles; applying a model derived by the AI app based on customer behavior and a set of features related to the case to classify each article of the merged pool of articles based at least in part on the predicted relevance of the article.Type: GrantFiled: September 24, 2018Date of Patent: February 14, 2023Assignee: salesforce.com, inc.Inventors: Pingping Xiu, Sitaram Asur, Anjan Goswami, Ziwei Chen, Na Cheng, Suhas Satish, Jacob Nathaniel Huffman, Peter Francis White, WeiPing Peng, Aditya Sakhuja, Jayesh Govindarajan, Edgar Gerardo Velasco
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Patent number: 11314790Abstract: Computing systems, database systems, and related methods are provided for recommending values for fields of database objects and dynamically updating a recommended value for a field of a database record in response to updated auxiliary data associated with the database record. One method involves obtaining associated conversational data, segmenting the conversational data, converting each respective segment of conversational data into a numerical representation, generating a combined numerical representation of the conversational data based on the sequence of numerical representations using an aggregation model, generating the recommended value based on the combined numerical representation of the conversational data using a prediction model associated with the field, and autopopulating the field of the case database object with the recommended value.Type: GrantFiled: April 28, 2020Date of Patent: April 26, 2022Assignee: salesforce.com, inc.Inventors: Son Thanh Chang, Weiping Peng, Na Cheng, Feifei Jiang, Jacob Nathaniel Huffman, Nandini Suresh Kumar, Khoa Le, Christopher Larry
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Patent number: 11061954Abstract: A data processing system analyzes a corpus of conversation data collected at an interactive conversation service to train an intent classification model. The intent classification model generates vectors based on the corpus of conversation data. A set of intents is selected and an intent seed input for each intent of the set of intents is input into the model to generate an intent vector corresponding to each intent. Vectors based on user inputs are generated and compared to the intent vectors to determine the intent.Type: GrantFiled: September 21, 2018Date of Patent: July 13, 2021Assignee: salesforce.com, inc.Inventors: Zachary Alexander, Naren M. Chittar, Alampallam R. Ramachandran, Anuprit Kale, Tiffany Deiandra McKenzie, Sitaram Asur, Jacob Nathaniel Huffman
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Patent number: 11061955Abstract: A data processing system analyzes a corpus of conversation data collected at an interactive conversation service to train an intent classification model. The intent classification model generates vectors based on the corpus of conversation data. A set of intents is selected and an intent seed input for each intent of the set of intents is input into the model to generate an intent vector corresponding to each intent. Vectors based on user inputs are generated and compared to the intent vectors to determine the intent.Type: GrantFiled: December 27, 2018Date of Patent: July 13, 2021Assignee: salesforce.com, inc.Inventors: Zachary Alexander, Naren M. Chittar, Alampallam R. Ramachandran, Anuprit Kale, Tiffany McKenzie, Sitaram Asur, Jacob Nathaniel Huffman
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Publication number: 20210149933Abstract: Computing systems, database systems, and related methods are provided for recommending values for fields of database objects and dynamically updating a recommended value for a field of a database record in response to updated auxiliary data associated with the database record. One method involves obtaining associated conversational data, segmenting the conversational data, converting each respective segment of conversational data into a numerical representation, generating a combined numerical representation of the conversational data based on the sequence of numerical representations using an aggregation model, generating the recommended value based on the combined numerical representation of the conversational data using a prediction model associated with the field, and autopopulating the field of the case database object with the recommended value.Type: ApplicationFiled: April 28, 2020Publication date: May 20, 2021Applicant: salesforce.com, Inc.Inventors: Son Thanh Chang, Weiping Peng, Na Cheng, Feifei Jiang, Jacob Nathaniel Huffman, Nandini Suresh Kumar, Khoa Le, Christopher Larry
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Patent number: 10853577Abstract: A data processing system analyzes a corpus of conversation data received at an interactive conversation service to train a response recommendation model. The response recommendation model generates response vectors based on custom responses and using the trained model and generates a context vector based on received input at the interactive conversation service. The context vector is compared to the set of response vectors to identify a set of recommended responses, which are recommended to an agent conversing with a user using the interactive conversation service.Type: GrantFiled: September 21, 2018Date of Patent: December 1, 2020Assignee: salesforce.com, inc.Inventors: Zachary Alexander, Jayesh Govindarajan, Peter White, Weiping Peng, Colleen Smith, Vishal Shah, Jacob Nathaniel Huffman, Alejandro Gabriel Perez Rodriguez, Edgar Gerardo Velasco, Na Cheng
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Publication number: 20200097496Abstract: A data processing system analyzes a corpus of conversation data collected at an interactive conversation service to train an intent classification model. The intent classification model generates vectors based on the corpus of conversation data. A set of intents is selected and an intent seed input for each intent of the set of intents is input into the model to generate an intent vector corresponding to each intent. Vectors based on user inputs are generated and compared to the intent vectors to determine the intent.Type: ApplicationFiled: December 27, 2018Publication date: March 26, 2020Inventors: Zachary Alexander, Naren M. Chittar, Alampallam R. Ramachandran, Anuprit Kale, Tiffany McKenzie, Sitaram Asur, Jacob Nathaniel Huffman
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Publication number: 20200097563Abstract: A data processing system analyzes a corpus of conversation data collected at an interactive conversation service to train an intent classification model. The intent classification model generates vectors based on the corpus of conversation data. A set of intents is selected and an intent seed input for each intent of the set of intents is input into the model to generate an intent vector corresponding to each intent. Vectors based on user inputs are generated and compared to the intent vectors to determine the intent.Type: ApplicationFiled: September 21, 2018Publication date: March 26, 2020Inventors: Zachary Alexander, Naren M. Chittar, Alampallam R. Ramachandran, Anuprit Kale, Tiffany Deiandra McKenzie, Sitaram Asur, Jacob Nathaniel Huffman
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Publication number: 20200097608Abstract: A method and system for recommending articles including: receiving a customer request from the customer during the session; generating case data for a case, by an article recommender app; configuring a training set based on the subject and description data of the customer request; identifying, by an artificial intelligence (AI) app, a first pool of articles from a knowledge database; identifying by at least one query, a second pool of articles from a case article database to into a merged pool of articles; assigning, by the AI app, an implicit label to one of the first pool and the second pool of the articles; applying a model derived by the AI app based on customer behavior and a set of features related to the case to classify each article of the merged pool of articles based at least in part on the predicted relevance of the article.Type: ApplicationFiled: September 24, 2018Publication date: March 26, 2020Inventors: Pingping XIU, Sitaram ASUR, Anjan GOSWAMI, Ziwei CHEN, Na CHENG, Suhas SATISH, Jacob Nathaniel HUFFMAN, Peter Francis WHITE, WeiPing PENG, Aditya SAKHUJA, Jayesh GOVINDARAJAN, Edgar Gerardo VELASCO
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Publication number: 20200097544Abstract: A data processing system analyzes a corpus of conversation data received at an interactive conversation service to train a response recommendation model. The response recommendation model generates response vectors based on custom responses and using the trained model and generates a context vector based on received input at the interactive conversation service. The context vector is compared to the set of response vectors to identify a set of recommended responses, which are recommended to an agent conversing with a user using the interactive conversation service.Type: ApplicationFiled: September 21, 2018Publication date: March 26, 2020Inventors: Zachary Alexander, Jayesh Govindarajan, Peter White, Weiping Peng, Colleen Smith, Vishal Shah, Jacob Nathaniel Huffman, Alejandro Gabriel Perez Rodriguez, Edgar Gerardo Velasco, Na Cheng