Abstract: Systems and methods are disclosed for initiating a monitoring session between a user device and a pet monitoring system including a base station and a plurality of monitoring devices. The base station receives a request to monitor the pet from the user device, activates the plurality of monitoring devices, receives data from the plurality of monitoring devices, locates the pet based on the received data from the plurality of monitoring devices, selects a selected monitoring device of the plurality of monitoring devices based upon at least one of the data from the plurality of monitoring devices and the location of the pet, and transmits the data from the selected monitoring device to the user device.

Abstract: A system for monitoring a pet includes a base station and a first monitoring device configured to capture first data relating to a first monitored area and to transmit the first data to the base station. The system further includes a second monitoring device configured to capture second data relating to a second monitored area and to transmit the second data to the base station, wherein the first monitored area and the second monitored area are adjacent. The base station is configured to determine a location of the pet as being in at least one of the first monitored area and the second monitored area. The base station is configured to determine a status of the pet based on at least one of the first and second data.

Abstract: A system for monitoring a pet includes a base station and a first monitoring device configured to capture first data relating to a first monitored area and to transmit the first data to the base station. The system further includes a second monitoring device configured to capture second data relating to a second monitored area and to transmit the second data to the base station, wherein the first monitored area and the second monitored area are adjacent. The base station is configured to determine a location of the pet as being in at least one of the first monitored area and the second monitored area. The base station is configured to determine a status of the pet based on at least one of the first and second data.

Abstract: A semantic reasoning engine is described for performing probabilistic reasoning over a semantic graph in a time-efficient and viable manner. The semantic reasoning engine includes a data store that provides the semantic graph, where the semantic graph is formed by a plurality of concepts connected together via probabilistic assertions. The semantic reasoning engine operates by providing an answer to a query by recursively collapsing the semantic graph based on at least one collapsing rule.

Abstract: Described is a technology for reducing the layout complexity of a graph, e.g., an STT graph. Nodes with similar incoming and outgoing links are grouped as candidate groupings to possibly be clustered. For each candidate grouping, if the nodes in the candidate grouping and/or the candidate grouping meet clustering criteria, the candidate grouping is clustered into a clustered node. The criteria may include user-specified parameters directed towards the nodes and/or the candidate groupings. For example, a node is removed from a group if the number of incoming links thereto or the number of outgoing links therefrom exceed maximum incoming and outgoing parameter values, respectively. A group is only clustered if the number of nodes therein meets a minimum size parameter.

Abstract: Described is a technology for composing queries by user interaction with objects and facets. A facet-based user interface allows users to select facets for use as filtering criteria, and a logic-based user interface allows users to logically combine object data. Query logic that processes the filtering criteria and/or logically combines the object data into a query. The facet-based user interface and logic-based user interface may be accessed via a unified user interface. The unified user interface may also provide a text editor for composing a text-based query.

Abstract: A computationally implemented method includes, but is not limited to: providing one or more relevant reported aspects associated with one or more source users that are relevant to achieving one or more target outcomes, the providing of the one or more relevant reported aspects being based, at least in part, on the one or more relevant reported aspects' association with the one or more source users; and developing one or more personalized plans designed to facilitate an end user to achieve the one or more target outcomes when one or more emulatable aspects indicated by the one or more personalized plans are emulated, the development of the one or more personalized plans being based, at least in part, on the providing In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: selecting at least one hypothesis from a plurality of hypotheses relevant to a user, the selection of the at least one hypothesis being based, at least in part, on at least one reported event associated with the user; and presenting one or more advisories related to the hypothesis. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: providing a plurality of relevant reported aspects associated with a plurality of source users that are relevant to achieving one or more target outcomes, the providing of the plurality of relevant reported aspects being based, at least in part, on relevancy of the plurality of relevant reported aspects with respect to the one or more target outcomes; and developing a template designed to facilitate one or more end users to achieve the one or more target outcomes when one or more emulatable aspects included in the template are emulated, the development of the template being based, at least in part, on the providing of the plurality of relevant reported aspects associated with the plurality of source users In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: receiving one or more requests indicating at least one or more target outcomes of one or more particular templates, the one or more particular templates designed to facilitate one or more end users to achieve the one or more target outcomes when one or more emulatable aspects included in the one or more particular templates are emulated; and providing from a plurality of templates the one or more particular templates, the providing being based at least on the one or more particular templates' association with the one or more target outcomes, the one or more particular templates developed based on one or more reported aspects of one or more source users In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: Described is a technology comprising a query processing pipeline in which a SPARQL query is processed into an intermediate LINQ query, which is then processed by a LINQ provider. The LINQ provider decides which instructions correspond to flat database queries, and routes those instructions a database engine (e.g., SQL server) for querying a database. Other instructions are provided to a reasoning engine for processing, e.g., by performing a graph traversal and/or database queries. The pipeline may include a parser that parses the query into an abstract syntax tree, and an optimizer that processes the abstract syntax tree into a LINQ query, including by reordering LINQ instructions and/or associating a flag with each of the instructions that indicates whether to query the database or provide the instruction to a reasoning engine.

Abstract: A computationally implemented method includes, but is not limited to: receiving a request for a personalized plan designed to facilitate an end user to achieve one or more target outcomes when one or more emulatable aspects indicated by the personalized plan are emulated, the request identifying at least a source user; acquiring source user data indicating a plurality of reported aspects associated with at least the source user in response to receiving the request; and developing the personalized plan by at least determining which of the plurality of reported aspects associated with the source user are relevant to the achievement of the one or more target outcomes. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: providing one or more relevant reported aspects associated with one or more source users that are relevant to achieving one or more target outcomes, the providing of the one or more relevant reported aspects being based, at least in part, on the one or more relevant reported aspects' association with the one or more source users; and developing one or more personalized plans designed to facilitate an end user to achieve the one or more target outcomes when one or more emulatable aspects indicated by the one or more personalized plans are emulated, the development of the one or more personalized plans being based, at least in part, on the providing In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: providing a plurality of relevant reported aspects associated with a plurality of source users that are relevant to achieving one or more target outcomes, the providing of the plurality of relevant reported aspects being based, at least in part, on relevancy of the plurality of relevant reported aspects with respect to the one or more target outcomes; and developing a template designed to facilitate one or more end users to achieve the one or more target outcomes when one or more emulatable aspects included in the template are emulated, the development of the template being based, at least in part, on the providing of the plurality of relevant reported aspects associated with the plurality of source users In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: identifying, in response to reception of one or more solicitations, one or more relevant reported aspects associated with one or more source users that are relevant to achieving one or more target outcomes, the identification of the one or more relevant reported aspects being based, at least in part, on relevancy of the one or more relevant reported aspects with respect to achieving the one or more target outcomes; and providing the one or more relevant reported aspects. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: determining whether a plurality of end users deviated from compliantly executing a template designed to facilitate the plurality of end users in achieving one or more target outcomes when one or more emulatable aspects included in the template are emulated by the plurality of end users, the one or more emulatable aspects being based on one or more relevant reported aspects of one or more source users that were deemed to have been relevant to achieving the one or more target outcomes; and modifying the template based, at least in part, on determining that the plurality of end users deviated from compliantly executing the template In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: determining whether a plurality of end users deviated from compliantly executing a template designed to facilitate the plurality of end users in achieving one or more target outcomes when one or more emulatable aspects included in the template are emulated by the plurality of end users, the one or more emulatable aspects being based on one or more relevant reported aspects of one or more source users that were deemed to have been relevant to achieving the one or more target outcomes; and modifying the template based, at least in part, on determining that the plurality of end users deviated from compliantly executing the template In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: receiving a request for a personalized plan designed to facilitate an end user to achieve one or more target outcomes when one or more emulatable aspects indicated by the personalized plan are emulated, the request identifying at least a source user; acquiring source user data indicating a plurality of reported aspects associated with at least the source user in response to receiving the request; and developing the personalized plan by at least determining which of the plurality of reported aspects associated with the source user are relevant to the achievement of the one or more target outcomes. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: detecting deviation from a compliant execution of a template by an end user, the template designed to facilitate the end user to achieve one or more target outcomes when one or more emulatable aspects included in the template are emulated, the one or more emulatable aspects being based on one or more relevant reported aspects of one or more source users that are relevant to achieving the one or more target outcomes; and executing one or more actions in response to the detecting of the deviation In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

Abstract: A computationally implemented method includes, but is not limited to: detecting deviation from a compliant execution of a template by an end user, the template designed to facilitate the end user to achieve one or more target outcomes when one or more emulatable aspects included in the template are emulated, the one or more emulatable aspects being based on one or more relevant reported aspects of one or more source users that are relevant to achieving the one or more target outcomes; and executing one or more actions in response to the detecting of the deviation In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.