Abstract: A method for generating synthetic data records which include datasets that capture state-based transitions, according to which a state transition family is randomly selecting, according to the distribution of samples between the different clusters of users and the context variables are randomly sampled according to their distribution within the chosen cluster. The relevant Markov Chains models are selected according to the sampled context and the initial state of the sequence is randomly selected according to the distribution of states. A random walk process is initialized on the graph models and the random walk is performed process on each context separately, assuming context independency. The cause condition of the current transition is sampled for each state transition, based on the distributions on the selected edge.

Abstract: A method for generating synthetic data records which include datasets that capture state-based transitions, according to which a state transition family is randomly selecting, according to the distribution of samples between the different clusters of users and the context variables are randomly sampled according to their distribution within the chosen cluster. The relevant Markov Chains models are selected according to the sampled context and the initial state of the sequence is randomly selected according to the distribution of states. A random walk process is initialized on the graph models and the random walk is performed process on each context separately, assuming context independency. The cause condition of the current transition is sampled for each state transition, based on the distributions on the selected edge.

Abstract: A system for generating fabricated pattern data records (XDRs) based on data from accessible data sources, which comprises an XDR core module containing one or more modeling and pattern creation modules for modeling original data received from the data sources; one or more synthetic data generation modules for generating fabricated data, based on the patterns created by the modeling and pattern creation modules; a data splitting module for splitting the data into training and testing sets according to a predetermined policy; an XDR storage database for storing created patterns and fabricated data; a configuration manager for controlling the operation of the modeling and pattern creation modules and of the synthetic data generation modules; a plurality of XDR agents being software components for communicating with the data sources and accessing relevant data, using a unique API of each data source.