公开(公告)号：US20200211035A1

公开(公告)日：2020-07-02

申请号：US16237339

申请日：2018-12-31

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jason Bluming ,  Avleen S. Bijral ,  Amrita Ray ,  Yan Guo ,  Xin Deng

IPC: G06Q30/02 ,  H04L29/08 ,  G06N20/00

Abstract: Disclosed are methods and systems for generating cure actions for improving a level of user engagement of a network. In some aspects, a method includes identifying network interaction relationships among a plurality of accounts of a computer network based on communication flows among the accounts, and tracking a level of engagement health of each of the accounts based on the interaction relationships over time. For each of the accounts, a determination is made as to whether the tracked level of engagement health meets a threshold requirement. For an account having a level of engagement health not meeting the threshold requirement, a cure action is selected based on one or more rules relating the tracked level of engagement health of the account to one or more predefined criteria. The cure action is then applied to the account.

公开(公告)号：US20190334759A1

公开(公告)日：2019-10-31

申请号：US15963865

申请日：2018-04-26

Applicant: Microsoft Technology Licensing, LLC

Inventor： Amrita Ray ,  Ross Faulkner Smith, JR. ,  Neil B. Ozzie ,  Ting Wei Lee ,  Xin Deng

IPC: H04L12/24 ,  G06F11/07 ,  G06F17/18 ,  H04L12/26

Abstract: Disclosed in some examples are technical solutions to the existing technical problems in computer-implemented identification of anomalous events for distributed unstructured data existing in current supervised and unsupervised approaches. The anomaly detection system may use one or more unsupervised approaches that factor in small data sets using a volume-based time-invariant model. In some examples, in addition, a cross-category proportionality based model may also be utilized.