Disclosed are a log parsing method and device, a server and a storage medium, relating to the field of network operation and maintenance. The method includes: acquiring (101) sample log data; performing (102) clustering processing on the sample log data according to the length of each sample log in the sample log data, and beginning and ending keywords of each sample log in the sample log data, to obtain a plurality of log clusters; determining (103) a quality score of each log cluster of the plurality of log clusters obtained by the clustering processing; and parsing (104) a log according to the plurality of log clusters and quality scores of the plurality of log clusters.

Provided are a time series data management unit that manages time series data generated in a target system, and a context management unit that manages a context registered by a user in association with time series data managed by a time series data management unit. The context management unit executes a process of extracting time series data associated with a context set as a search target by the user out of the managed time series data.

Telematics data, including geolocation data, may be collected, monitored, measured, and/or generated by one or more processors communicatively coupled with memory and associated with a mobile, machine, and/or vehicle device. Telematics data may also be collected from one or more external vendors. Geolocation data pertaining to the mobile, machine and/or vehicle device may be analyzed to derive valuable information on the presence, dwell times, and movements of human beings. For example, a rate of human beings, such as, e.g., the cars in which they are driving or riding, traversing an area at specific times of day and days of the week can be inferred. In some cases, this information may also be used to plan and adapt highway systems, construction plans, and business plans. Significant reductions in vehicle emissions can be achieved, congestion can be limited, safety can be enhanced, and travel times reduced by helping commuters and other drivers choose uncongested routes to their destinations.

Methods and systems disclosed herein relate generally to systems and methods for using a machine-learning model to predict user-engagement levels of users in response to presentation of future interactive content. A content provider system accesses a machine-learning model, which was trained using a training dataset including previous user-device actions performed by a plurality of users in response to previous interactive content. The content provider system receives user-activity data of a particular user and applies the machine-learning model to the user-activity data, in which the user-activity data includes user-device actions performed by the particular user in response to interactive content. The machine-learning model generates an output including a categorical value that represents a predicted user-engagement level of the particular user in response to a presentation of the future interactive content.

An object is to provide an information processing apparatus capable of analyzing operation log data that can be acquired through a digital device and effectively using the operation log data. An information processing apparatus (10) according to the present disclosure includes an information collection unit (11) configured to collect an operation log generated when a digital device is operated from a plurality of the digital devices, an execution unit (12) configured to co-cluster operator information and content information. The operator information is for identifying an operator of the digital device included in a plurality of the operation logs, and the content information is about content viewed by the operator using the digital device, and a post-processing unit (13) configured to create confirmation data using an execution result of the co-clustering.

An example embodiment involves rules related to repairing software programs, wherein the rules associate indications of software program failures with repair applications that are configured to correct the software program failures. One or more processors are configured to: (i) receive, by a predictive model, a representation of an execution history of a particular software program, wherein the predictive model has been trained on a corpus of execution histories of the software programs; (ii) generate, by the predictive model and from the execution history, a failure prediction for the particular software program; (iii) receive, by an automated repair controller application, the failure prediction from the predictive model; (iv) based on applying the rules to the failure prediction, determine, by the automated repair controller application, a repair application from the repair applications; and (v) cause, by the automated repair controller application, the repair application to be executed within the network.

Methods, devices and computer program products for data analysis are provided. For example, a method comprises: in response to receiving target data from a target sensor at a first time, determining one or more reference sensors based on location information of a neighbor sensor adjacent to the target sensor and a second time of receiving the latest data from the neighbor sensor; determining reference estimation data of the one or more reference sensors at the first time based on historical sensor data obtained from the one or more reference sensors; determining target estimation data of the target sensor at the first time based on the reference estimation data; and detecting abnormity of the target data based on the target data and the target estimation data. In this way, abnormity of the sensor data may be detected efficiently and accurately.

A system for monetizing animal data includes a source of animal data that can be transmitted electronically. Characteristically, the source of animal data includes at least one sensor. An intermediary server receives and collects the animal data such that collected data has attached thereto metadata. The metadata includes at least one of the origination of the animal data or personal attributes of individuals from which the animal data originated. The intermediary server provides requested animal data to a data acquirer for consideration. The requested animal data may include simulated animal data. The intermediary server will also distribute at least a portion of the consideration to at least one stakeholder. The intermediary server includes a single computer server or a plurality of interacting computer servers.

Auditing information is captured from a processing stack of an invoked application. An annotation customized for that invocation context is processed to filter and/or add additional audition information available from the processing stack. The customized auditing information is then sent to a destination based on a processing context of the invoked application when the invoked application completes processing. In an embodiment, the customized auditing information is housed in a data store and an interface is provided for customized query processing, report processing, event processing, a notification processing.

An information handling system may include a processor, a management controller communicatively coupled to the processor and configured for out-of-band management of the information handling system, and a smart network interface card communicatively coupled to the processor and the management controller and configured to receive telemetry information from telemetry sources of the information handling system and perform advanced processing of the telemetry information.