公开(公告)号：US10664764B2

公开(公告)日：2020-05-26

申请号：US15161855

申请日：2016-05-23

Applicant: Arizona Board of Regents on behalf of Arizona State University

Inventor： Pritam Gundecha ,  Jiliang Tang ,  Huan Liu

IPC: G06N20/00

Abstract: Embodiments of a system for determining personal attributes based on public interaction data are illustrated. In one embodiment, the system employs a process for predicting personal attributes based on public interaction data by constructing matrices based on user interactions drawn from public posts on a social media website. The process may further learn a compact representation for a plurality of users based on public posts using the matrices, extract the compact representation of one or more users that have been labeled, and apply a classifier to learn about a particular personal attribute. Through this, a prediction of personal attributes of users that have not been labeled may be obtained.

公开(公告)号：US20170212943A1

公开(公告)日：2017-07-27

申请号：US15412955

申请日：2017-01-23

Applicant: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY

Inventor： Jundong Li ,  Xia Hu ,  Jiliang Tang ,  Huan Liu

IPC: G06F17/30

CPC classification number: G06F16/248 ,  G06F16/22 ,  G06F16/24568 ,  G06F16/24578 ,  G06F16/9024 ,  G06F16/9535

Abstract: Systems and methods for exploiting link information in streaming feature selection, resulting in a novel unsupervised streaming feature selection framework are disclosed.

公开(公告)号：US20170004403A1

公开(公告)日：2017-01-05

申请号：US15161855

申请日：2016-05-23

Applicant: Arizona Board of Regents on behalf of Arizona State University

Inventor： Pritam Gundecha ,  Jiliang Tang ,  Huan Liu

IPC: G06N5/04 ,  G06N99/00

CPC classification number: G06N20/00

Abstract: Embodiments of a system for determining personal attributes based on public interaction data are illustrated. In one embodiment, the system employs a process for predicting personal attributes based on public interaction data by constructing matrices based on user interactions drawn from public posts on a social media website. The process may further learn a compact representation for a plurality of users based on public posts using the matrices, extract the compact representation of one or more users that have been labeled, and apply a classifier to learn about a particular personal attribute. Through this, a prediction of personal attributes of users that have not been labeled may be obtained.

Abstract translation: 示出了基于公共交互数据来确定个人属性的系统的实施例。 在一个实施例中，该系统采用基于公共交互数据来预测个人属性的过程，该过程是通过基于社交媒体网站上的公开帖子中提取的用户交互构建矩阵来构建矩阵。 该过程可以基于使用矩阵的公共帖子进一步学习多个用户的紧凑表示，提取已标记的一个或多个用户的紧凑表示，并应用分类器来了解特定个人属性。 通过这样，可以获得未被标记的用户的个人属性的预测。

公开(公告)号：US10942939B2

公开(公告)日：2021-03-09

申请号：US15412955

申请日：2017-01-23

Applicant: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY

Inventor： Jundong Li ,  Xia Hu ,  Jiliang Tang ,  Huan Liu

IPC: G06F17/00 ,  G06F7/00 ,  G06F16/248 ,  G06F16/22 ,  G06F16/901 ,  G06F16/2455 ,  G06F16/2457 ,  G06F16/9535

Abstract: Systems and methods for exploiting link information in streaming feature selection, resulting in a novel unsupervised streaming feature selection framework are disclosed.

公开(公告)号：US20170213153A1

公开(公告)日：2017-07-27

申请号：US15412909

申请日：2017-01-23

Applicant: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY

Inventor： Suhang Wang ,  Jiliang Tang ,  Huan Liu

IPC: G06N99/00 ,  G06F17/30

CPC classification number: G06N20/00 ,  G06F16/283 ,  G06F16/285

Abstract: Systems and methods for executing an unsupervised feature selection algorithm on a processor which directly embeds feature selection into a clustering algorithm using sparse learning are disclosed. The direct embedding of the feature selection, via sparse learning, reduces storage requirement of collected data. In one method, unsupervised feature selection may be accomplished through a removal of redundant, irrelevant, and/or noisy features of incoming high-dimensional data.