公开(公告)号：US11061955B2

公开(公告)日：2021-07-13

申请号：US16233420

申请日：2018-12-27

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Naren M. Chittar ,  Alampallam R. Ramachandran ,  Anuprit Kale ,  Tiffany McKenzie ,  Sitaram Asur ,  Jacob Nathaniel Huffman

IPC: G06F16/35 ,  G06T11/20 ,  G06N20/00 ,  G06F16/332 ,  G06F16/33

Abstract: 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.

公开(公告)号：US20200097563A1

公开(公告)日：2020-03-26

申请号：US16138514

申请日：2018-09-21

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Naren M. Chittar ,  Alampallam R. Ramachandran ,  Anuprit Kale ,  Tiffany Deiandra McKenzie ,  Sitaram Asur ,  Jacob Nathaniel Huffman

IPC: G06F17/30

Abstract: 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.

公开(公告)号：US11580179B2

公开(公告)日：2023-02-14

申请号：US16139386

申请日：2018-09-24

Applicant: salesforce.com, inc.

Inventor： 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

IPC: G06N5/00 ,  G06F16/9535 ,  G06F16/35 ,  G06F16/338 ,  H04L67/63

Abstract: 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.

公开(公告)号：US20210149933A1

公开(公告)日：2021-05-20

申请号：US15929364

申请日：2020-04-28

Applicant: salesforce.com, Inc.

Inventor： Son Thanh Chang ,  Weiping Peng ,  Na Cheng ,  Feifei Jiang ,  Jacob Nathaniel Huffman ,  Nandini Suresh Kumar ,  Khoa Le ,  Christopher Larry

IPC: G06F16/31 ,  H04L12/58 ,  G06F16/34 ,  G06F16/35

Abstract: 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.

公开(公告)号：US20200097544A1

公开(公告)日：2020-03-26

申请号：US16138662

申请日：2018-09-21

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Jayesh Govindarajan ,  Peter White ,  Weiping Peng ,  Colleen Smith ,  Vishal Shah ,  Jacob Nathaniel Huffman ,  Alejandro Gabriel Perez Rodriguez ,  Edgar Gerardo Velasco ,  Na Cheng

IPC: G06F17/27 ,  G06N3/08 ,  G06N3/04

Abstract: 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.

公开(公告)号：US20200097496A1

公开(公告)日：2020-03-26

申请号：US16233420

申请日：2018-12-27

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Naren M. Chittar ,  Alampallam R. Ramachandran ,  Anuprit Kale ,  Tiffany McKenzie ,  Sitaram Asur ,  Jacob Nathaniel Huffman

IPC: G06F16/35 ,  G06T11/20 ,  G06F16/33 ,  G06F16/332 ,  G06N20/00

Abstract: 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.

公开(公告)号：US11314790B2

公开(公告)日：2022-04-26

申请号：US15929364

申请日：2020-04-28

Applicant: salesforce.com, Inc.

Inventor： Son Thanh Chang ,  Weiping Peng ,  Na Cheng ,  Feifei Jiang ,  Jacob Nathaniel Huffman ,  Nandini Suresh Kumar ,  Khoa Le ,  Christopher Larry

IPC: G06F16/00 ,  G06N20/00 ,  G06F16/31 ,  G06F16/35 ,  G06F16/34 ,  H04L51/56 ,  G06F16/2457 ,  G06F16/2455 ,  G06F16/9535

Abstract: 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.

公开(公告)号：US11061954B2

公开(公告)日：2021-07-13

申请号：US16138514

申请日：2018-09-21

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Naren M. Chittar ,  Alampallam R. Ramachandran ,  Anuprit Kale ,  Tiffany Deiandra McKenzie ,  Sitaram Asur ,  Jacob Nathaniel Huffman

IPC: G06F16/35 ,  G06F16/61 ,  G06F16/33

Abstract: 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.

公开(公告)号：US10853577B2

公开(公告)日：2020-12-01

申请号：US16138662

申请日：2018-09-21

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Jayesh Govindarajan ,  Peter White ,  Weiping Peng ,  Colleen Smith ,  Vishal Shah ,  Jacob Nathaniel Huffman ,  Alejandro Gabriel Perez Rodriguez ,  Edgar Gerardo Velasco ,  Na Cheng

IPC: G06F40/30 ,  G06N3/04 ,  G06N3/08 ,  G06F40/35 ,  G06F3/0484

Abstract: 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.