Servicenow, Inc.

Brian Robert Silverstein

James Crotinger

Dariush Shahgoshtasbi

Qingbin Li

Lorne Schell

Yujie Fang

Katrina Suzanne Stankiewicz

Darren Hou

Fanny Riols

Systems and methods are provided that include accessing a representation of a network that includes a plurality of elements; generating a plurality of clusters representative of the network, each cluster of the plurality of clusters including a respective non-overlapping subset of elements of the plurality of elements; obtaining, for each element of the subset of elements of a particular cluster of the plurality of clusters, historical data indicative of operation of at least two of the respective elements of the particular cluster; training, using the historical data, a model to detect anomalous activity in the particular cluster; obtaining operational data for a particular element of the subset of elements of the particular cluster; and determining, by applying the model to the operational data, that the particular element of the cluster exhibits anomalous activity.

Network anomaly detection using clustering

Origin text content to be analyzed using natural language processing is received. The received origin text content is preprocessed using one or more processors including by vectorizing at least a portion of the received origin text content and identifying a closest matching centroid to automatically generate a reduced version of the origin text content to assist in satisfying a constraint of a natural language processing model. The reduced version of the origin text content is used as an input to the natural language processing model. A result of the natural language processing model is provided for use in managing a computerized workflow.

Labeled clustering preprocessing for natural language processing

Origin text content to be analyzed using natural language processing is received. A two-dimensional item sequence representation for at least a portion of the received origin text content is generated. Using one or more processors, one or more evaluation metrics are determined based on an analysis of the two-dimensional item sequence representation. A reduced version of the origin text content is automatically generated based on the one or more evaluation metrics to assist in satisfying a constraint of a natural language processing model. The reduced version of the origin text content is used as an input to the natural language processing model.

Multi-dimensional N-gram preprocessing for natural language processing

A computing device is provided that is configured to obtain, from a managed network, a plurality of response times of a network-based service provided by the managed network; to train, based on the plurality of response times, a probability distribution to model the managed network; to receive an additional response time from the managed network; to use the probability distribution to determine, for the additional response time, a percentile based on the additional response time; based on the percentile, to determine that the additional response time is anomalously high with respect to the plurality of response times of the network-based service; and to transmit, to a client device associated with the managed network, an indication that the additional response time is anomalously high. The probability distribution includes a central portion based on a plurality of bins and a tail portion based on a parametric distribution.

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Seattle, WA, United States of America

Brian Robert Silverstein