Abstract: A method is described for obtaining and using viewership data to determine relationships between previous viewership of an episodic program and viewership of future episodes of the program. Aggregating the data may comprise determining missing data points and predicting substitute data points based on past viewership data for the individual viewer and a plurality of other viewers. Data may be presented to the user in a number of ways to aid in analysis and planning of likely viewership for a season of a television program. Data may be used to optimize advertising revenues, plan television lineups to maximize a number of likely viewers, or allocate content and resources between broadcast and video-on-demand.

Abstract: A method is described for obtaining and using viewership data to determine relationships between previous viewership of an episodic program and viewership of future episodes of the program. Aggregating the data may comprise determining missing data points and predicting substitute data points based on past viewership data for the individual viewer and a plurality of other viewers. Data may be presented to the user in a number of ways to aid in analysis and planning of likely viewership for a season of a television program. Data may be used to optimize advertising revenues, plan television lineups to maximize a number of likely viewers, or allocate content and resources between broadcast and video-on-demand.

Abstract: A System is monitored by detecting activity signatures of network components. Some of the activity signatures are generated by sensing patterns of operations in data streams. Some of the activity signatures are precompiled in the system, or are standard in computer systems. The activity signatures are stored in a database. Select information about select baselined attributes generates monitoring profiles (MPs) for the baselined attributes. The MPs are defined so abnormal behavior of end points and/or system components can be detected. The system compiles baseline values for baselined attributes of MP's. By properly analyzing deviating end points or components one can determine what is causing a problem or who is effected by a problem based on which identifying attributes are common to the deviating end points or components.

Abstract: A first embodiment of the system and method of this invention is disclosed in a distributed computer system. The system is monitored by detecting activity signatures of individually identifiable network components, programs and/or PCs by sensing operations (keystrokes on a keyboard or mouse clicks) and/or codes embedded in data streams in the system. The activity signatures can be defined by result-specific character sets and are generated or provided for identifying the various activities of the system. After the activity signatures are generated, select information about select baselined attributes of activities detected by their activity signatures are measured and compiled in a database, and monitoring profiles (MPs) for the baselined attributes of activities are generated. The MPs are defined by a group of identifying attribute values of end-points so abnormal behavior of end-points/components can later be detected. For example, a disconnected server associated with a group of terminals can be detected.

Abstract: A System is monitored by detecting activity signatures of network components. Some of the activity signatures are generated by sensing patterns of operations in data streams. Some of the activity signatures are precompiled in the system, or are standard in computer systems. The activity signatures are stored in a database. Select information about select baselined attributes generates monitoring profiles (MPs) for the baselined attributes. The MPs are defined so abormal behavior of end points and/or system components can be detected. The system compiles baseline values for baselined attributes of MP's. By properly analyzing deviating end points or components one can determine what is causing a problem or who is effected by a problem based on which identifying attributes are common to the deviating end points or components.

Abstract: A method for analyzing service in a mobile communication network includes estimating probabilities of handover of a mobile unit from each of a plurality of cells in the network to each other cell in the plurality. Based on the probabilities of handover, a respective steady-state probability is found that the mobile unit is served by each of one or more of the cells.