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：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.