公开(公告)号：US11010548B2

公开(公告)日：2021-05-18

申请号：US16839192

申请日：2020-04-03

申请人： AT&T Intellectual Property I, L.P.

发明人： Pamela Bogdan ,  Gary Gressel ,  Gary Reser ,  Alex Rubarkh ,  Kenneth Shirley

IPC分类号： G06F40/00 ,  G06F40/216 ,  G06F16/28 ,  G06F16/35 ,  G06F40/30

摘要： Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.

公开(公告)号：US20210232764A1

公开(公告)日：2021-07-29

申请号：US17232546

申请日：2021-04-16

申请人： AT&T Intellectual Property I, L.P.

发明人： Pamela Bogdan ,  Gary Gressel ,  Gary Reser ,  Alex Rubarkh ,  Kenneth Shirley

IPC分类号： G06F40/216 ,  G06F16/28 ,  G06F16/35 ,  G06F40/30

摘要： Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.

公开(公告)号：US20200234005A1

公开(公告)日：2020-07-23

申请号：US16839192

申请日：2020-04-03

申请人： AT&T Intellectual Property I, L.P.

发明人： Pamela Bogdan ,  Gary Gressel ,  Gary Reser ,  Alex Rubarkh ,  Kenneth Shirley

IPC分类号： G06F40/216 ,  G06F40/30 ,  G06F16/35 ,  G06F16/28

摘要： Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.

公开(公告)号：US20190272320A1

公开(公告)日：2019-09-05

申请号：US16299871

申请日：2019-03-12

申请人： AT&T Intellectual Property I, L.P.

发明人： Pamela A. M. Bogdan ,  Gary Gressel ,  Gary Reser ,  Alex Rubarkh ,  Kenneth Shirley

IPC分类号： G06F17/27 ,  G06F16/28 ,  G06F16/35

摘要： Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.