Abstract: The current document is directed to computationally efficient, robust, and accurate methods and systems that determine the heartbeat rate of human subjects, patients, and/or participants monitored by a video-recording-capable device or system by analyzing video recordings of human subjects, patients, and/or participants, either in real time or following video recording. The currently disclosed methods and systems employ face-recognition methods to identify adaptive regions of interest corresponding to facial-skin areas. Spatial averages of the intensities of light components with different frequencies reflected from the identified adaptive regions of interest are extracted from the video recording as intensity signals. The intensity signals are then analyzed to extract detrended, band-pass-filtered oscillating light-intensity signals that are processed by spectral and peak-finding methods that each produces a determined heartbeat rate for each of multiple time intervals.

Abstract: The current document is directed to a methods and systems that use observational data collected by various devices and sensors to generate electronic-data representations of human conversations. The implementations of these methods and systems, disclosed in the current document, provide a highly extensible and generic platform for converting observational data into affect-annotated-timeline outputs that provide both a textual transcription of a conversation and a parallel set of affect annotations to the conversation. The affect-annotated-timeline outputs may be useful to researchers and developers, but also serve as inputs to any of a wide variety of downstream analytical processes and analysis systems that are, in turn, incorporated into many different types of special-purpose analysis and control systems.

Abstract: The current document is directed to methods and systems that provide an emotional compass that reflects the emotional states of human beings, dynamics of the emotional states over time periods, emotional synchronization between humans and between humans and automated interactive systems, and the degree to which the emotional state of one human is influenced or affected by the emotional state of another human or by an automated interactive system. The emotional compass can be used for continuous or intermittent emotional orientation by both automated systems and human analysts. The emotional awareness provided by the emotional compass facilitates continuous or intermittent strategy selection for achieving various different types of emotion-related results.

Abstract: The current document is directed to a methods and systems that use observational data collected by various devices and sensors to generate electronic-data representations of human conversations. The implementations of these methods and systems, disclosed in the current document, provide a highly extensible and generic platform for converting observational data into affect-annotated-timeline outputs that provide both a textual transcription of a conversation and a parallel set of affect annotations to the conversation. The affect-annotated-timeline outputs may be useful to researchers and developers, but also serve as inputs to any of a wide variety of downstream analytical processes and analysis systems that are, in turn, incorporated into many different types of special-purpose analysis and control systems.

Abstract: The current document is directed to a methods and systems that use observational data collected by various devices and sensors to generate electronic-data representations of human conversations. The implementations of these methods and systems, disclosed in the current document, provide a highly extensible and generic platform for converting observational data into affect-annotated-timeline outputs that provide both a textual transcription of a conversation and a parallel set of affect annotations to the conversation. The affect-annotated-timeline outputs may be useful to researchers and developers, but also serve as inputs to any of a wide variety of downstream analytical processes and analysis systems that are, in turn, incorporated into many different types of special-purpose analysis and control systems.

Abstract: The current document is directed to a relationship-analysis system. The currently disclosed relationship-analysis system collects objective and subjective observations of participants, and their relationship, in an interaction or transaction. The objective and subjective observations are combined to generate an observation data set that is processed by a computational relationship-analysis system. The analysis produces a variety of different types of results, including trust metrics, and stores the results in memory and/or mass-storage for control of downstream analysis, reporting, and actions. Trust metrics provide a basis for carrying out numerous types of downstream actions and for generating recommendations and evaluations by various types of relationship-evaluation and relationship-management systems that employ the relationship-analysis system.

Abstract: The current document is directed to a relationship-analysis system. The currently disclosed relationship-analysis system collects objective and subjective observations of participants, and their relationship, in an interaction or transaction. The objective and subjective observations are combined to generate an observation data set that is processed by a computational relationship-analysis system. The analysis produces a variety of different types of results, including trust metrics, and stores the results in memory and/or mass-storage for control of downstream analysis, reporting, and actions. Trust metrics provide a basis for carrying out numerous types of downstream actions and for generating recommendations and evaluations by various types of relationship-evaluation and relationship-management systems that employ the relationship-analysis system.

Abstract: The current document is directed to a relationship-analysis system. The currently disclosed relationship-analysis system collects objective and subjective observations of participants, and their relationship, in an interaction or transaction. The objective and subjective observations are combined to generate an observation data set that is processed by a computational relationship-analysis system. The analysis produces a variety of different types of results, including trust metrics, and stores the results in memory and/or mass-storage for control of downstream analysis, reporting, and actions. Trust metrics provide a basis for carrying out numerous types of downstream actions and for generating recommendations and evaluations by various types of relationship-evaluation and relationship-management systems that employ the relationship-analysis system.

Abstract: The current document is directed to methods and systems that provide optimal or near-optimal resource-exchange operation through configuration and control of resource exchanges. These methods and systems employ a number of currently disclosed optimization tools, including dimensional reduction of attribute vectors corresponding to resource-exchange entities, scoring resources with respect to their ease or likelihood of matching to resource users, and providing optimal or near-optimal attribute values for attribute vectors corresponding to resource-exchange entities. These optimization tools facilitate development of a wide variety of different types of resource-exchange-operation-improvement and resource-exchange-optimization methods and systems, including methods and systems for configuring resource exchanges to improve and/or optimize their operational behaviors.

Abstract: The current document is directed to automated market-segment-discovery methods and systems that may be incorporated within, or used in combination with, various types of analysis and optimization automated systems for automated discovery of market segments for subsequent use in targeted marketing and information distribution. In one implementation, a log of visitor records collected by an analysis and/or optimization system is processed to generate a segment-discovery tree. Construction of the segment-discovery tree produces a set of candidate market-segment-defining rules. Various different techniques and metrics can be applied to produce a set of market-segment-defining rules from these candidate rules. The market-segment-defining rules can then be exported to marketing systems or subsystems to facilitate targeted marketing and information distribution.

Abstract: The current document is directed to methods and systems that receive instrumentation-generated events and that employ statistical inference to discover event topics and to assign an action to each of a number of events and that use the actions to predict future events and actions. In a described implementation, accumulated action messages are used to build a predictive model for each monitored website and the predictive model is used, in turn, to predict future actions based on already received actions.

Abstract: The current document is directed to methods and systems that receive instrumentation-generated events and that employ statistical inference to discover event topics and to assign a topic or category to each of a number of events. In a described implementation, the events comprise key/value pairs. A seeded local/global-topic latent Dirichlet allocation methods is used to discover topics and assign topics to a set of events. The topic-assigned events are then processed to generate topic signatures, using which the methods and systems assign topics to subsequently received messages.

Abstract: The current document is directed to methods and systems that receive instrumentation-generated events and that employ statistical inference to discover event topics and to assign an action to each of a number of events and that use the actions to predict future events and actions. In a described implementation, accumulated action messages are used to build a predictive model for each monitored website and the predictive model is used, in turn, to predict future actions based on already received actions.

Abstract: The current document is directed to automated electronic testing, optimization, and/or analysis systems that perform testing that results in non-binomial experimental results that are processed by using efficient and robust processing methods. In one implementation, efficient and robust processing methods are employed to process non-binomial results produced from single-factor tests. In a second implementation, robust and computationally efficient processing methods are employed to analyze non-binomial results from multi-factor/multi-level tests.

Abstract: The current document is directed to methods and systems that receive instrumentation-generated events and that employ statistical inference to discover event topics and to assign a topic or category to each of a number of events. In a described implementation, the events comprise key/value pairs. A seeded local/global-topic latent Dirichlet allocation methods is used to discover topics and assign topics to a set of events. The topic-assigned events are then processed to generate topic signatures, using which the methods and systems assign topics to subsequently received messages.

Abstract: The current document is directed to automated market-segment-discovery methods and systems that may be incorporated within, or used in combination with, various types of analysis and optimization automated systems for automated discovery of market segments for subsequent use in targeted marketing and information distribution. In one implementation, a log of visitor records collected by an analysis and/or optimization system is processed to generate a segment-discovery tree. Construction of the segment-discovery tree produces a set of candidate market-segment-defining rules. Various different techniques and metrics can be applied to produce a set of market-segment-defining rules from these candidate rules. The market-segment-defining rules can then be exported to marketing systems or subsystems to facilitate targeted marketing and information distribution.

Abstract: Certain embodiments of the present invention are directed to test-duration estimation. A time needed to run an automated web-page test, or the remaining time needed to complete the automated web-page test, is estimated by estimating a sample size needed to ensure that observed differences in conversion rates are attributable, with a specified statistical significance, to selecting particular factor levels for particular factors that are varied during the automated testing. The estimated sample size is then divided by an average web-page access rate to obtain the remaining testing time to achieve a specified significance level.

Abstract: The current document is directed to automated electronic testing, optimization, and/or analysis systems that perform testing that results in non-binomial experimental results that are processed by using efficient and robust processing methods. In one implementation, efficient and robust processing methods are employed to process non-binomial results produced from single-factor tests. In a second implementation, robust and computationally efficient processing methods are employed to analyze non-binomial results from multi-factor/multi-level tests.

Abstract: The current application is directed to methods and systems that accumulate data with respect to the time behavior of posts related to one or more pages of an individual or organization within a social network and generate one or more models that characterize the time behavior of posts within the social network. These models, or heuristics based on these models, can be used to estimate characteristics and parameters of the time behaviors of individual posts prior to posting or at various times following posting of the posts to social-network pages.

Abstract: Certain embodiments of the present invention are directed to test-duration estimation. A time needed to run an automated web-page test, or the remaining time needed to complete the automated web-page test, is estimated by estimating a sample size needed to ensure that observed differences in conversion rates are attributable, with a specified statistical significance, to selecting particular factor levels for particular factors that are varied during the automated testing. The estimated sample size is then divided by an average web-page access rate to obtain the remaining testing time to achieve a specified significance level.