Cisco Technology, Inc.

Pengfei Sun

Qihong Shao

David C White, Jr

Gurvinder Singh

Daniel Shan-Shea Chen

Methods are provided for generating digests of network-related notifications specifically tailored to user's personas and adaptable across multiple timescale frequencies. Specifically, the methods involve obtaining user data of a user associated with an enterprise network and a plurality of network-related notifications. Each of the plurality of network-related notifications relates to network operations or network configurations. The methods further involve determining a network persona of the user in a context of the enterprise network based on the user data and generating a digest of the plurality of network-related notifications based on the network persona. The digest includes a semantic summary for each of the plurality of network-related notifications that is specific to the network persona. The methods further involve providing the digest for performing one or more actions associated with the enterprise network.

Persona-based multi-scale network related digest generation

A heterogeneous graph learning system generates and analyzes network implementations. The heterogeneous graph learning system includes obtaining information describing multiple network implementations including heterogeneous nodes. The heterogeneous graph learning system also includes generating a one-hop graph connecting a particular node of the heterogeneous nodes with a set of related nodes. The one-hop graph connects the particular node with the set of related nodes via corresponding edges. The heterogeneous graph learning system further includes transforming the one-hop graph into a weighted graph based on a Dynamic Meta Path Transformation (DMPT). In the DMPT, each of the corresponding edges connecting the particular node to a corresponding related node among the set of related nodes is associated with a corresponding weight.

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Reno, NV, United States of America

Pengfei Sun