Abstract: Systems, methods, and devices for determining contexts and determining associated health profiles using information received from multiple health sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of time and location. Health sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The health sensor data can include health sensor readings that are implicit indications of health for the context. The sensor data can also include user reported data with explicit descriptions of health for the context. The health sensor data can be filtered by context data according a selected context. The filtered sensor data can then be analyzed to determine a health profile for the context that can be output to one or more users or entities.

Abstract: Systems, methods, and devices for determining contexts and determining associated emotion profiles using information received from multiple emotion sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of times and locations. Emotion sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The emotion sensor data can include emotion sensor readings that are implicit indications of an emotion for the context. The sensor data can also include user reported data with explicit descriptors of an emotion for the context. The emotion sensor data can be filtered by context data according a selected context. The filtered sensor data can then be analyzed to determine an emotion profile for the context that can be output to one or more users or entities.

Abstract: While a user views a primary content item (for example, a movie on a television screen), secondary content items are selected and presented to the user, either on the same screen or on a screen of the user's companion device. To choose selections that are relevant to the user's current interests, the selection process considers information beyond the realm of primary and secondary content. Over time, the selection process learns to make more relevant selections by monitoring selection choices made by other systems.

Abstract: A mobile communication device includes wireless local area network (WLAN) baseband hardware with at least one WLAN transceiver; non-volatile, non-transitory memory that stores a transportation model based on aggregated basic service set identification (BSSID) information collected from a plurality of WLAN access points; at least one sensor that is operative to detect motion of the mobile communication device; and at least one processor, operatively coupled to the WLAN baseband hardware, the memory and to the at least one sensor. The at least one processor is operative to determine that the mobile communication device is located on public transportation using the transportation model in response to a motion detection signal received from the at least one sensor.

Abstract: A mobile communication device includes wireless local area network (WLAN) baseband hardware with at least one WLAN transceiver; non-volatile, non-transitory memory that stores a transportation model based on aggregated basic service set identification (BSSID) information collected from a plurality of WLAN access points; at least one sensor that is operative to detect motion of the mobile communication device; and at least one processor, operatively coupled to the WLAN baseband hardware, the memory and to the at least one sensor. The at least one processor is operative to determine that the mobile communication device is located on public transportation using the transportation model in response to a motion detection signal received from the at least one sensor.

Abstract: A system and method for identifying and labeling locations frequented by a user of a device, where the system and method track geographic positions and environmental or contextual factors as the user moves about, and identify locations of interest to the user via a clustering procedure. As the device collects contextual data, the system and method label each identified location to create a location model. This model allows the device to label new locations as they arise. The model may be periodically updated by separately processing geographic position data gathered after the model was created to determine if the cluster locations and labels remain accurate.

Abstract: A system and method for identifying and labeling locations frequented by a user of a mobile communication device track geographic positions and environmental or contextual factors as the user moves about, and identify locations of interest to the user via a clustering procedure. As the device collects contextual data, the system and method label each identified location to create a location model. This model allows the device to label new locations as they arise. The model may be periodically updated by separately processing geographic position data gathered after the model was created to determine if the cluster locations and labels remain accurate.

Abstract: User-preference datapoints are collected. At least some of these datapoints are associated with user-preference information about an item (e.g., a movie), and some of these datapoints are associated with user-preference information about an attribute (e.g., a movie genre or an actor). A profile of the user is created based, at least in part, on these datapoints. When a new datapoint is collected, the new datapoint is assigned a user-preference “score.” If, for example, the new datapoint does not come with an explicit user-preference rating, then the score is based on related item and attribute datapoints already in the profile. Depending upon the relationship of the new datapoint to the already existing datapoints, a confidence value is assigned to the user-preference score. The profile is then updated with the new datapoint along with its assigned score and confidence rating. The user profile can be used in performing any number of actions.

Abstract: Systems, methods, and devices for determining contexts and determining associated demographic profiles using information received from multiple demographic sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of time and location. Demographic sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The demographic sensor data can include demographic sensor readings that are implicit indications of a demographic for the context. The sensor data can also include user reported data with explicit descriptions of a demographic for the context. The demographic sensor data can be filtered by context data according a selected context.

Abstract: Systems, methods, and devices for determining contexts and determining associated health profiles using information received from multiple health sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of time and location. Health sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The health sensor data can include health sensor readings that are implicit indications of health for the context. The sensor data can also include user reported data with explicit descriptions of health for the context. The health sensor data can be filtered by context data according a selected context. The filtered sensor data can then be analyzed to determine a health profile for the context that can be output to one or more users or entities.

Abstract: Systems, methods, and devices for determining contexts and determining associated emotion profiles using information received from multiple emotion sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of times and locations. Emotion sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The emotion sensor data can include emotion sensor readings that are implicit indications of an emotion for the context. The sensor data can also include user reported data with explicit descriptors of an emotion for the context. The emotion sensor data can be filtered by context data according a selected context. The filtered sensor data can then be analyzed to determine an emotion profile for the context that can be output to one or more users or entities.

Abstract: Systems, methods, and devices for determining contexts and determining associated demographic profiles using information received from multiple demographic sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of time and location. Demographic sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The demographic sensor data can include demographic sensor readings that are implicit indications of a demographic for the context. The sensor data can also include user reported data with explicit descriptions of a demographic for the context. The demographic sensor data can be filtered by context data according a selected context.

Abstract: Disclosed are methods and apparatus for processing linguistic expressions (e.g., opinionated text documents). The linguistic expressions are processed by, firstly, detecting topics of interest discussed in the linguistic expressions. The sentiment, or sentiments, of an originator with respect to each of the topics detected in the linguistic expressions is then assessed. The originators are then grouped (or clustered) into one or more groups based on the similarities between the originators' respective sets of detected topics and corresponding sentiments. Semantic information is then associated with a given group. Finally, for a given member of a given group, a profile is created or updated. This profile comprises attributes that may be based on a degree of membership of the given member to the given group and the semantic information associated with the given group.

Abstract: User-preference datapoints are collected. At least some of these datapoints are associated with user-preference information about an item (e.g., a movie), and some of these datapoints are associated with user-preference information about an attribute (e.g., a movie genre or an actor). A profile of the user is created based, at least in part, on these datapoints. When a new datapoint is collected, the new datapoint is assigned a user-preference “score.” If, for example, the new datapoint does not come with an explicit user-preference rating, then the score is based on related item and attribute datapoints already in the profile. Depending upon the relationship of the new datapoint to the already existing datapoints, a confidence value is assigned to the user-preference score. The profile is then updated with the new datapoint along with its assigned score and confidence rating. The user profile can be used in performing any number of actions.

Abstract: While a user views a primary content item (for example, a movie on a television screen), secondary content items are selected and presented to the user, either on the same screen or on a screen of the user's companion device. To choose selections that are relevant to the user's current interests, the selection process considers information beyond the realm of primary and secondary content. Over time, the selection process learns to make more relevant selections by monitoring selection choices made by other systems.

Abstract: Disclosed are methods and apparatus for processing linguistic expressions (e.g., opinionated text documents). The linguistic expressions are processed by, firstly, detecting topics of interest discussed in the linguistic expressions. The sentiment, or sentiments, of an originator with respect to each of the topics detected in the linguistic expressions is then assessed. The originators are then grouped (or clustered) into one or more groups based on the similarities between the originators' respective sets of detected topics and corresponding sentiments. Semantic information is then associated with a given group. Finally, for a given member of a given group, a profile is created or updated. This profile comprises attributes that may be based on a degree of membership of the given member to the given group and the semantic information associated with the given group.

Abstract: A Higher Order Command Dialog System (HOCS) 250 for enabling voice control to a user interface is provided. The HOCS can record (302) a sequence of action steps a user performs while navigating a menu system to perform a task, prompt (304) a user to create an HOC for the task, and associate (306) the sequence of actions steps with a Higher Order Command (HOC) for performing the task. The HOC can include multi-modal inputs (120/260) and prompt a user for non-specific additional information (124) required in performing the task. The HOCS can store the HOC as a voice tag or a user-input command.