Abstract: A system for analyzing service usage utilizing Markov models. Records of client requests to the service are extracted from at least one log. The records are grouped by client and sorted by timestamp. A pattern of requests that form an action is detected. Each action has a time. A probability is calculated of a transition from a precedent action to a subsequent action, where the precedent action has a time prior to the subsequent action. A delay time is also calculated between a precedent action and a subsequent action. A probability is calculated for a delay time, such as the likelihood that a delay from a precedent action to a subsequent action will fall within a given time interval.

Abstract: A system for analyzing service usage utilizing Markov models. Records of client requests to the service are extracted from at least one log. The records are grouped by client and sorted by timestamp. A pattern of requests that form an action is detected. Each action has a time. A probability is calculated of a transition from a precedent action to a subsequent action, where the precedent action has a time prior to the subsequent action. A delay time is also calculated between a precedent action and a subsequent action. A probability is calculated for a delay time, such as the likelihood that a delay from a precedent action to a subsequent action will fall within a given time interval.

Abstract: A system for analyzing service usage utilizing Markov models. Records of client requests to the service are extracted from at least one log. The records are grouped by client and sorted by timestamp. A pattern of requests that form an action is detected. Each action has a time. A probability is calculated of a transition from a precedent action to a subsequent action, where the precedent action has a time prior to the subsequent action. A delay time is also calculated between a precedent action and a subsequent action. A probability is calculated for a delay time, such as the likelihood that a delay from a precedent action to a subsequent action will fall within a given time interval.

Abstract: A system for analyzing service usage utilizing Markov models. Records of client requests to the service are extracted from at least one log. The records are grouped by client and sorted by timestamp. A pattern of requests that form an action is detected. Each action has a time. A probability is calculated of a transition from a precedent action to a subsequent action, where the precedent action has a time prior to the subsequent action. A delay time is also calculated between a precedent action and a subsequent action. A probability is calculated for a delay time, such as the likelihood that a delay from a precedent action to a subsequent action will fall within a given time interval.