公开(公告)号：US20160246896A1

公开(公告)日：2016-08-25

申请号：US14628070

申请日：2015-02-20

Applicant: XEROX CORPORATION

Inventor： Akhil Arora ,  Sainyam Galhotra ,  Shourya Roy ,  Srinivas Virinchi

IPC: G06F17/30

CPC classification number: G06F16/9535 ,  G06Q50/01

Abstract: The disclosed embodiments illustrate methods and systems for identifying one or more target users, of a first content, from a social network. The disclosed method includes generating a graph comprising one or more nodes, representative of one or more users of the social network, and one or more edges connecting the one or more nodes. Thereafter, a first set of nodes is selected from the one or more nodes based on at least a first score and/or a second score. Finally, a third set of nodes is selected from the first set of nodes based on at least a polarity score associated with a second set of nodes, determined based on at least a first weight and a second weight, connected to each node in the first set of nodes, wherein the third set of nodes represents the one or more target users.

Abstract translation: 所公开的实施例示出了用于从社交网络识别第一内容的一个或多个目标用户的方法和系统。 所公开的方法包括生成包括表示社交网络的一个或多个用户的一个或多个节点以及连接该一个或多个节点的一个或多个边缘的图形。 此后，基于至少第一分数和/或第二分数从一个或多个节点中选择第一组节点。 最后，基于至少基于至少第一权重和第二权重确定的与第二组节点相关联的极性分数，从第一组节点中选择第三组节点，连接到第一节点中的每个节点 一组节点，其中第三组节点表示一个或多个目标用户。

公开(公告)号：US20170278010A1

公开(公告)日：2017-09-28

申请号：US15077085

申请日：2016-03-22

Applicant: XEROX CORPORATION

Inventor： Narayanan Unny Edakunni ,  Sainyam Galhotra

IPC: G06N99/00 ,  G06Q30/00 ,  H04L12/26

CPC classification number: G06N20/00 ,  G06N5/04 ,  G06N7/005 ,  G06Q30/016 ,  H04L41/147 ,  H04L41/16

Abstract: The disclosed embodiments illustrate methods and systems for prediction of a communication channel for communication with customer service. The method includes monitoring, by one or more sensors in a server, a communication involving at least a first user for a pre-defined time period. The one or more types of communication channels being used by at least the first user over the pre-defined time period and/or the one or more types of problems reported by at least the first user, is monitored. The method further includes generating, by one or more processors of the server, a temporal data based on the monitoring. The classifier is trained by the one or more processors, based on the generated temporal data. The classifier predicts a likelihood of selection of a type of communication channels from the one or more types of communication channels, for communication between the first user and the server.