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：US11507617B2

公开(公告)日：2022-11-22

申请号：US16685933

申请日：2019-11-15

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Na Cheng

IPC: G06F16/61 ,  G06F40/30 ,  G06F7/08

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for extracting topics from a corpus of exchanges. The system generates vector representations of utterances of an entity common to the exchanges and uses the vector representations to cluster the utterances. The system labels the clusters and uses the labeled clusters to generate an exchange label sequence for each of the exchanges, where each exchange label sequence corresponds to a sequence of utterances generated by the entity. The system processes the exchange label sequences to generate one or more subsets of the utterances, where each of the subsets corresponds to a particular topic.

公开(公告)号：US20210150144A1

公开(公告)日：2021-05-20

申请号：US17099083

申请日：2020-11-16

Applicant: Salesforce.com, Inc.

Inventor： Anuprit KALE ,  Weiping Peng ,  Na Cheng ,  Rick Lindstrom ,  Zachary Alexander

IPC: G06F40/289 ,  G06F16/33 ,  G06F16/31 ,  G06F16/332

Abstract: DESCRIBED HEREIN ARE SYSTEMS, APPARATUS, METHODS AND COMPUTER PROGRAM PRODUCTS FOR MACHINE LEARNING INTENT CLASSIFICATION. IN VARIOUS EMBODIMENTS, HISTORICAL UTTERANCES PROVIDED BY USERS MAY BE UTILIZED FOR BOT TRAINING. CONTEXT AND PERSONALLY IDENTIFIABLE INFORMATION MAY BE REMOVED FROM THE UTTERANCES. THE UTTERANCES MAY BE ASSOCIATED WITH VECTORS. THE UTTERANCES AND VECTORS MAY BE USED TO DETERMINE RECOMMENDATIONS.

公开(公告)号：US20210149949A1

公开(公告)日：2021-05-20

申请号：US16685933

申请日：2019-11-15

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Na Cheng

IPC: G06F16/61 ,  G06F7/08 ,  G06F40/30

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for extracting topics from a corpus of exchanges. The system generates vector representations of utterances of an entity common to the exchanges and uses the vector representations to cluster the utterances. The system labels the clusters and uses the labeled clusters to generate an exchange label sequence for each of the exchanges, where each exchange label sequence corresponds to a sequence of utterances generated by the entity. The system processes the exchange label sequences to generate one or more subsets of the utterances, where each of the subsets corresponds to a particular topic.

公开(公告)号：US10565265B2

公开(公告)日：2020-02-18

申请号：US15292033

申请日：2016-10-12

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Scott Thurston Rickard, Jr. ,  Clifford Z. Huang ,  J. Justin Donaldson

IPC: G06F17/30 ,  G06F16/93

Abstract: A document retrieval system tracks user selections of documents from query search results and uses the selections as proxies for manual user labeling of document relevance. The system trains a model representing the significance of different document features when calculating true document relevance for users. To factor in positional biases inherent in user selections in search results, the system learns positional bias values for different search result positions, such that the positional bias values are accounted for when computing document feature features that are used to compute true document relevance.

公开(公告)号：US11651237B2

公开(公告)日：2023-05-16

申请号：US15721346

申请日：2017-09-29

Applicant: salesforce.com, inc.

Inventor： Scott Thurston Rickard, Jr. ,  Elizabeth Rachel Balsam ,  Tracy Morgan Backes ,  Zachary Alexander

IPC: G06Q30/02 ,  G06N20/10 ,  G06N5/022 ,  G06N20/00 ,  G06N5/00 ,  G06N20/20 ,  G06Q30/0201 ,  G06Q30/0203 ,  G06Q30/0204 ,  G06N3/08 ,  G06N7/00

CPC classification number: G06N5/022 ,  G06N5/003 ,  G06N20/00 ,  G06N20/20 ,  G06Q30/0201 ,  G06Q30/0203 ,  G06Q30/0204 ,  G06N3/08 ,  G06N7/005 ,  G06N20/10

Abstract: An online system stores objects representing potential transactions of an enterprise. The online system uses predictor models to determine an aggregate score based on values of the objects associated with a time interval, for example, a month. Each object is configured to take one of a plurality of states. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data for generating the predictor models. The online system categorizes the objects into bins based on states of the objects. The online system may generate different predictions for each category. The online system may use machine learning based models as predictor models. The online system extracts features describing potential transaction objects and provides these as input to the predictor model.

公开(公告)号：US20210150146A1

公开(公告)日：2021-05-20

申请号：US16687626

申请日：2019-11-18

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Edgar Gerardo Velasco ,  Victor Winslow Yee ,  Na Cheng ,  Khoa Le

IPC: G06F40/30 ,  G06F16/33 ,  G06F16/332 ,  G06N20/00

Abstract: A system is configured to analyze a corpus of historical chat data to identify the list of “best” responses. As such, the user is not required to identify a list of canned responses for input into the system. The described system uses a context word embedding function and response word embedding function to generate context vectors and response vectors corresponding to the corpus of conversation data, and the vectors are represented by a respective context matrix and a response matrix. The system processes these matrices to generate scores for responses, clusters the responses, and identifies the responses corresponding to the best scores for each cluster.

公开(公告)号：US20210149921A1

公开(公告)日：2021-05-20

申请号：US16685926

申请日：2019-11-15

Applicant: salesforce.com, inc.

Inventor： Zachary Alexander ,  Na Cheng

IPC: G06F16/28 ,  G06F16/21 ,  G06N7/00 ,  G06N3/00 ,  G06F17/27

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for extracting state flow structures from a corpus of exchanges. The system generates vector representations of utterances of an entity common to the exchanges and uses the vector representations to cluster the utterances.
The system labels the clusters and uses the labeled clusters to generate an exchange label sequence for each of the exchanges, where the exchange label sequence corresponds to a sequence of utterances generated by the entity. The system processes the exchange label sequences to generate a state flow structure, where each of the states is represented by a corresponding set of utterances.

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.