公开(公告)号：US09294631B1

公开(公告)日：2016-03-22

申请号：US14262606

申请日：2014-04-25

Applicant: Amdocs Software Systems Limited

Inventor： Peter John Cogan ,  John Henry Hannon ,  Michael Richard Kerrigan

IPC: H04M15/00

CPC classification number: H04L41/0631 ,  G06F17/16 ,  H04M15/58 ,  H04M15/70

Abstract: A system, method, and computer program product are provided for identification of common root causes with sequential patterns. In use, a plurality of customer event sequences are identified. Additionally, the plurality of customer event sequences are grouped into a hierarchical framework of patterns. Further, a root-cause analysis (RCA) is performed for the customer event sequences utilizing the hierarchical framework of patterns.

Abstract translation: 提供了一种系统，方法和计算机程序产品，用于以顺序模式识别常见的根本原因。 在使用中，识别出多个客户事件序列。 另外，多个客户事件序列被分组成模式的分层框架。 此外，利用模式的分层框架，为客户事件序列执行根本原因分析（RCA）。

公开(公告)号：US10402737B1

公开(公告)日：2019-09-03

申请号：US14521380

申请日：2014-10-22

Applicant: Amdocs Software Systems Limited

Inventor： Leon Malalel ,  Peter John Cogan

IPC: G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00 ,  G06N7/00 ,  H04L29/08

Abstract: A system, method, and computer program product are provided for providing proactive customer care for issues associated with billing or ordering processes. In use, a likelihood that a customer is going to call a call center to address at least one issue associated with at least one of an ordering process or a billing process is predicted. Additionally, it is determined whether the customer is likely to call the call center based on the predicted likelihood that the customer is going to call the call center. Further, the customer is proactively notified before the customer contacts the call center, if it is determined that the customer is likely to call the call center.

公开(公告)号：US09729571B1

公开(公告)日：2017-08-08

申请号：US14815715

申请日：2015-07-31

Applicant: Amdocs Software Systems Limited

Inventor： Paul Andrew Ferguson ,  Roman Ferrando Llopis ,  Peter John Cogan

IPC: H04L29/06 ,  H04L12/715

CPC classification number: H04L63/1441 ,  H04L45/46 ,  H04L47/2441 ,  H04L63/1408 ,  H04L63/306

Abstract: A system, method, and computer program product are provided for detecting and measuring changes in network behavior of communication networks utilizing real-time clustering algorithms. In use, network traffic associated with at least one communication network is received. Additionally, the network traffic is characterized and classified based on similarities in the network traffic utilizing one or more real-time clustering algorithms. Further, changes in network behavior of the at least one communication network are detected and measured utilizing information associated with the classified network traffic.