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SYSTEMS AND METHODS FOR CAUSAL CHANGE ANALYSIS OF INCIDENTS

发明专利审中
10浏览
20权利要求 · 3 独立
§ Ⅰ

卷宗概要

发明人

Najah GHALYAN; Mohammed AYUB; Richard AMOAKO; David ALGORRY; Senad IBRAIMOSKI; Alexandru-Petre CAZAN; Alejandro CARRASCOSA; Franco HORISBERGER; Edward FUNNELL; Sean MORAN; Sean GUARNACCIO; Zafer ERDOGAN

IPC 分类

G6F 16/2455G6F 16/242G6F 16/248

CPC 分类

G6F16/2455G6F16/242G6F16/248

A method may include: receiving an identification of a current incident involving an affected element; generating a first Structured Query Language (SQL) query for recently-implemented change records for the affected element; executing the first SQL query on a database; receiving the recently-implemented change records for the affected element; generating a second SQL query for past incidents that are similar to the current incident; executing the second SQL query on the database; receiving the past incidents that are similar to the current incident, together with associated change records that were identified to be a cause of the past incidents; calculating a relevance score of each recently-implemented change record to the current incident, based on a similarity of the past change records that caused similar incidents; and returning the past change record for the affected element that is similar to the past change record for any element with a highest score.

原文(中文)

A method may include: receiving an identification of a current incident involving an affected element; generating a first Structured Query Language (SQL) query for recently-implemented change records for the affected element; executing the first SQL query on a database; receiving the recently-implemented change records for the affected element; generating a second SQL query for past incidents that are similar to the current incident; executing the second SQL query on the database; receiving the past incidents that are similar to the current incident, together with associated change records that were identified to be a cause of the past incidents; calculating a relevance score of each recently-implemented change record to the current incident, based on a similarity of the past change records that caused similar incidents; and returning the past change record for the affected element that is similar to the past change record for any element with a highest score.