distributed systems user behavior model neural networks
Issue Date:
2008
Publisher:
Institute of Information Theories and Applications FOI ITHEA
Abstract:
We present a complex neural network model of user behavior in distributed systems. The model
reflects both dynamical and statistical features of user behavior and consists of three components: on-line and
off-line models and change detection module. On-line model reflects dynamical features by predicting user
actions on the basis of previous ones. Off-line model is based on the analysis of statistical parameters of user
behavior. In both cases neural networks are used to reveal uncharacteristic activity of users. Change detection
module is intended for trends analysis in user behavior. The efficiency of complex model is verified on real data of
users of Space Research Institute of NASU-NSAU.
