Abstract: The described technology is generally directed towards methods for data latency evaluation. The techniques disclosed herein can provide useful information about when a data consumer can expect to receive data. Methods can create and compare data latency cumulative probability distributions comprising probabilities associated with different latency values, at various different levels of completeness.

Abstract: The described technology is generally directed towards methods for data latency evaluation. The techniques disclosed herein can provide useful information about when a data consumer can expect to receive data. Methods can create and compare data latency cumulative probability distributions comprising probabilities associated with different latency values, at various different levels of completeness.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system collects information associated with trouble tickets each including a problem abstract and a log text. The method includes analyzing the log text to obtain a problem resolution for that ticket; defining ticket clusters according to the problem abstracts, and labeling the clusters. The processing system creates a library of the labeled clusters, each entry including a cluster label, a problem abstract for that cluster, and a resolution summary for that problem abstract, indicating a mapping of the problem abstract to the resolution summary for that cluster. The method includes training, based on the mapping, machine-learning applications for a predicted resolution summary for each cluster and for classifying a new ticket. The method includes assigning the new ticket to a cluster according to the classifying. Other embodiments are disclosed.

Abstract: The described technology is generally directed towards methods for data latency evaluation. The techniques disclosed herein can provide useful information about when a data consumer can expect to receive data. Methods can create and compare data latency cumulative probability distributions comprising probabilities associated with different latency values, at various different levels of completeness.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system collects information associated with trouble tickets each including a problem abstract and a log text. The method includes analyzing the log text to obtain a problem resolution for that ticket; defining ticket clusters according to the problem abstracts, and labeling the clusters. The processing system creates a library of the labeled clusters, each entry including a cluster label, a problem abstract for that cluster, and a resolution summary for that problem abstract, indicating a mapping of the problem abstract to the resolution summary for that cluster. The method includes training, based on the mapping, machine-learning applications for a predicted resolution summary for each cluster and for classifying a new ticket. The method includes assigning the new ticket to a cluster according to the classifying. Other embodiments are disclosed.

Abstract: A processing system including at least one processor may detect the presence of at least two users in a zone containing a network-connected device, obtain preferences and tolerance ranges of the at least two users with respect to the network-connected device, select a setting for the network-connected device in accordance with the preferences and tolerance ranges of the at least two users, and apply the setting to the network-connected device. The processing system may further detect a change of the setting, and adjust at least one of the preferences and tolerance ranges of the at least two users in response to the change of the setting.

Abstract: A processing system including at least one processor may detect the presence of at least two users in a zone containing a network-connected device, obtain preferences and tolerance ranges of the at least two users with respect to the network-connected device, select a setting for the network-connected device in accordance with the preferences and tolerance ranges of the at least two users, and apply the setting to the network-connected device. The processing system may further detect a change of the setting, and adjust at least one of the preferences and tolerance ranges of the at least two users in response to the change of the setting.