MATRIX FACTORIZATION FOR USER PROFILING AND OUTLIER DETECTION IN ACTIVITY DATA
摘要:
A method for inferring user activity statistics includes receiving job logs of a device infrastructure. Each job log including job information for a job performed for one of a set of users by one of a plurality of shared devices. A job descriptor is generated for each job based on the job log. The job is assigned to one of a set of defined job types based on the job descriptor. An activity matrix is composed where activity of each user for each of a plurality of time periods is represented as a fixed-length vector representing at least some of the job types. Each index of the vector is derived from a count of one job type for the user in that time period. The activity matrix is decomposed into first and second factor matrices to minimize an overall reconstruction error. User activity statistics are output based on the decomposition.
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