Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.