Abstract: Apparatus, systems, and/or methods may provide travel assistance. For example, a determination may be made that a user is to begin driving in the near future. In addition, a determination may be made of one or more predicted destinations when the user is to begin driving in the near future. Thus, travel assistance may be provided to the user based on the one or more predicted destinations when the user is to begin driving in the near future.

Abstract: Apparatus, systems, and/or methods may provide travel assistance. For example, a determination may be made that a user is to begin driving in the near future. In addition, a determination may be made of one or more predicted destinations when the user is to begin driving in the near future. Thus, travel assistance may be provided to the user based on the one or more predicted destinations when the user is to begin driving in the near future.

Abstract: A system for filtering device information to be provided to a user by a digital device or system according to physiological information collected from the user. The physiological information may be used to determine the user's present cognitive stress, wherein the device information may be prioritized, withheld, delayed, or deleted if the present cognitive stress exceeds a predetermined threshold. The device information may be further evaluated with contextual information such as different aspects of the device information or non-physiological user information (e.g. location, time of the day). The system may manage device information with minimal or less user interaction than user defined rule systems.

Abstract: Various systems and methods for processing activity data with a knowledge engine to generate actionable insights for a human subject are described. These actionable insights may include identifying a most likely action given a particular state of the human subject, identifying a most likely state in which the human subject performs a particular activity, or identifying anomalies in human activity patterns. In an example, an electronic processing system operates the knowledge engine with operations that: identify patterns of activity using clustering of events, identify meaningful patterns of activity from the patterns of activity based on co-occurrence of characteristics for respective events, rank the identified meaningful patterns of activity based on confidence and support of respective patterns to occur for a human subject, and generate a personalization action (such as an action for a software application) based on the ranked, identified meaningful patterns of activity.

Abstract: Methods, apparatus, and system to parse an unstructured, natural language input of a user, infer a semantic meaning of an intent of the user, and determine a present or future user state, including a location and a time, in which the intent can be fulfilled.

Abstract: Methods, apparatus, and system to parse an unstructured, natural language input of a user, infer a semantic meaning of an intent of the user, and determine a present or future user state, including a location and a time, in which the intent can be fulfilled.

Abstract: Apparatus, systems, and/or methods may provide travel assistance. For example, a determination may be made that a user is to begin driving in the near future. In addition, a determination may be made of one or more predicted destinations when the user is to begin driving in the near future. Thus, travel assistance may be provided to the user based on the one or more predicted destinations when the user is to begin driving in the near future.

Abstract: Methods, apparatus, and system to parse an unstructured, natural language input of a user, infer a semantic meaning of an intent of the user, and determine a present or future user state, including a location and a time, in which the intent can be fulfilled.

Abstract: Apparatus, systems, and/or methods may provide travel assistance. For example, a determination may be made that a user is to begin driving in the near future. In addition, a determination may be made of one or more predicted destinations when the user is to begin driving in the near future. Thus, travel assistance may be provided to the user based on the one or more predicted destinations when the user is to begin driving in the near future.

Abstract: Various systems and methods for evaluating event importance are described herein. A system for evaluating event importance includes a processor subsystem; and a memory coupled to the processor subsystem, the memory including instructions, which when executed by the processor subsystem, cause the processor subsystem to: access data related to a prior event attended by a user; access data related to an upcoming event; and use the data related to the prior event and the data related to the upcoming event in a machine learning subsystem to determine an importance score of the upcoming event.

Abstract: A system for filtering device information to be provided to a user by a digital device or system according to physiological information collected from the user. The physiological information may be used to determine the user's present cognitive stress, wherein the device information may be prioritized, withheld, delayed, or deleted if the present cognitive stress exceeds a predetermined threshold. The device information may be further evaluated with contextual information such as different aspects of the device information or non-physiological user infomiation (e.g. location, time of the day). The system may manage device information with minimal or less user interaction than user defined rule systems.

Abstract: Apparatuses, systems and methods associated with mode of transportation recommendation are disclosed herein. In embodiments, a device may include communication circuitry to communicate with a server and a user interface to interact with a user of the device. The device may further include an analyzer to identify a future trip to be travelled by the user, and identify a destination associated with the future trip. The device may further include a recommendation engine to transmit, to the server, a recommendation trigger message that includes an indication of the destination; receive, from the server, an indication of a mode of transportation to the destination, the indication of the mode of transportation based on prior trip information of the user; and cause a notification for use of the mode of transportation to the destination to be indicated by the user interface. Other embodiments may be described and/or claimed.

Abstract: Methods, apparatus, and system to parse an unstructured, natural language input of a user, infer a semantic meaning of an intent of the user, and determine a present or future user state, including a location and a time, in which the intent can be fulfilled.

Abstract: Various systems and methods for processing activity data with a knowledge engine to generate actionable insights for a human subject are described. These actionable insights may include identifying a most likely action given a particular state of the human subject, identifying a most likely state in which the human subject performs a particular activity, or identifying anomalies in human activity patterns. In an example, an electronic processing system operates the knowledge engine with operations that: identify patterns of activity using clustering of events, identify meaningful patterns of activity from the patterns of activity based on co-occurrence of characteristics for respective events, rank the identified meaningful patterns of activity based on confidence and support of respective patterns to occur for a human subject, and generate a personalization action (such as an action for a software application) based on the ranked, identified meaningful patterns of activity.

Abstract: Disclosed methods, systems, and storage media provide state-based time/task management interfaces. A computer device may determine various user states and user intents, and generate an instance of a graphical user interface (GUI) comprising objects and semantic time anchors. Each object may correspond to a user intent and each semantic time anchor may be associated with a user state. The computer device may obtain a first input comprising a selection of an object and obtain a second input comprising a selection of a semantic time anchor. The computer device may generate another instance of the GUI to indicate an association of the selected object with the selected semantic time anchor. The computer device may generate a notification to indicate a user intent of the selected object upon occurrence of a state that corresponds with the selected semantic time anchor. Other embodiments may be described and/or claimed.

Abstract: System and techniques for context enhanced indexing are described herein. A document change event may be obtained. A context of the document change event may be captured. Here, the context pertains to an entity responsible for the document change event. Then, an index to correlate a context element of the context to a document of the document change event may be stored.

Abstract: Apparatus, systems, and/or methods may provide travel assistance. For example, a determination may be made that a user is to begin driving in the near future. In addition, a determination may be made of one or more predicted destinations when the user is to begin driving in the near future. Thus, travel assistance may be provided to the user based on the one or more predicted destinations when the user is to begin driving in the near future.

Abstract: An exercise schedule optimizer system includes a user interface to receive data input from an exerciser and provide data output to the exerciser. The system also includes an exercise goal generator to generate an exercise goal based on at least data regarding the exerciser, an exercise schedule proposer to propose one or more exercise schedule proposals based on at least a historical exercise pattern of the exerciser, and an optimal exercise scheduler to determine an optimal exercise schedule based on at least the one or more exercise schedule proposals.

Abstract: An event schedule optimizer system includes a user interface, an invitees extractor, a time optimizer, and a place optimizer. The user interface is to receive data input from an organizer and provide data output to the organizer. The invitees extractor is to generate an intended invitees list including intended invitees for a target event based on the data input from the organizer. The time optimizer is to determine an optimal time period for the target event based on a list of historical events of the organizer. The place optimizer is to determine an optimal place for the target event based on a set of proposed times and the list of historical events of the organizer.

Abstract: An embodiment of the invention provides a gesture recognition system (GRS) that displays a graphical user interface in which symbols are grouped into “pods” on a display screen, and a user enters a desired symbol into a computer by selecting a pod containing the desired symbol, and then selecting the symbol from a display of the symbols in the selected pod using hand motions without having to contact the display screen or use a manual controller.