Abstract: Subject matter involves using natural language to Web application program interfaces (API), which map natural language commands into API calls, or API commands. This mapping enables an average user with little or no programming expertise to access Web services that use API calls using natural language. An API schema is accessed and using a specialized grammar, with the help of application programmers, canonical commands associated with the API calls are generated. A hierarchical probabilistic distribution may be applied to a semantic mesh associated with the canonical commands to identify elements of the commands that require labeling. The identified elements may be sent to annotators, for labeling with NL phrases. Labeled elements may be applied to the semantic mesh and probabilities, or weights updated. Labeled elements may be mapped to the canonical commands with machine learning to generate a natural language to API interface. Other embodiments are described and claimed.

Abstract: Aspects of the present disclosure relate to obtaining task and/or list information from various types of media files. In examples, an image of an environment may be obtained, where the image may include a depiction of a plurality of tasks. The tasks may be extracted from the image and assigned to one or more users based contextual information within the image. In some examples, tasks within an image may be identified based on positional information of the text and/or character delimiters. In some examples, audio information may be received and processed such that the audio information is converted to text. The text may then be parsed to extract one or more items of a list and/or one or more tasks.

Abstract: Subject matter involves using natural language to Web application program interfaces (API), which map natural language commands into API calls, or API commands. This mapping enables an average user with little or no programming expertise to access Web services that use API calls using natural language. An API schema is accessed and using a specialized grammar, with the help of application programmers, canonical commands associated with the API calls are generated. A hierarchical probabilistic distribution may be applied to a semantic mesh associated with the canonical commands to identify elements of the commands that require labeling. The identified elements may be sent to annotators, for labeling with NL phrases. Labeled elements may be applied to the semantic mesh and probabilities, or weights updated. Labeled elements may be mapped to the canonical commands with machine learning to generate a natural language to API interface. Other embodiments are described and claimed.

Abstract: Subject matter involves using natural language to Web application program interfaces (API), which map natural language commands into API calls, or API commands. This mapping enables an average user with little or no programming expertise to access Web services that use API calls using natural language. An API schema is accessed and using a specialized grammar, with the help of application programmers, canonical commands associated with the API calls are generated. A hierarchical probabilistic distribution may be applied to a semantic mesh associated with the canonical commands to identify elements of the commands that require labeling. The identified elements may be sent to annotators, for labeling with NL phrases. Labeled elements may be applied to the semantic mesh and probabilities, or weights updated. Labeled elements may be mapped to the canonical commands with machine learning to generate a natural language to API interface. Other embodiments are described and claimed.

Abstract: Subject matter involves using natural language to Web application program interfaces (API), which map natural language commands into API calls, or API commands. This mapping enables an average user with little or no programming expertise to access Web services that use API calls using natural language. An API schema is accessed and using a specialized grammar, with the help of application programmers, canonical commands associated with the API calls are generated. A hierarchical probabilistic distribution may be applied to a semantic mesh associated with the canonical commands to identify elements of the commands that require labeling. The identified elements may be sent to annotators, for labeling with NL phrases. Labeled elements may be applied to the semantic mesh and probabilities, or weights updated. Labeled elements may be mapped to the canonical commands with machine learning to generate a natural language to API interface. Other embodiments are described and claimed.

Abstract: Electronic messages are automatically debugged. An electronic message sent by a sender to one or more recipients is received and analyzed to identify any issues in the message. Whenever one or more issues are identified in the message, a reply message may be sent to the sender that describes each of the identified issues and includes a proposed fix for each of the identified issues. Each of the issues identified in the message may also be fixed resulting in a fixed version of the message, and the fixed version of the message may be sent to the sender for their approval. The fixed version of the message may also be sent to each of the recipients. Whenever no issues are identified in the message, a reply message may be sent to the sender informing them that no issues were found.

Abstract: Systems and methods are presented for detecting an action intent within received content, identifying an action completion bot for carrying out the corresponding action, and initiating the action through an action request to the action completion bot. An action delegation agent executing on a computer system, receives notice of received content, where the action delegation agent is not the target of the received content. An analysis of the received content is conducted to identify an action intent of the received content. Based on the action intent, an action registry is consulted to identify a corresponding action completion bot for carrying out the intended action. A request is submitted to the action completion hot to carry out the action.

Abstract: Multidimensional search capabilities are enabled on a non-PC (personal computer) device being utilized by a user. An original query submitted by the user via the non-PC device is received. A structured data repository is accessed to extract structured data that is available for the original query, where the extracted structured data represents attributes of the original query. The extracted structured data is provided to the user in the form of a hierarchical menu which allows the user to interactively modify the original query, such modification resulting in a revised query.

Abstract: Multidimensional search capabilities are enabled on a non-PC (personal computer) device being utilized by a user. An original query submitted by the user via the non-PC device is received. A structured data repository is accessed to extract structured data that is available for the original query, where the extracted structured data represents attributes of the original query. The extracted structured data is provided to the user in the form of a hierarchical menu which allows the user to interactively modify the original query, such modification resulting in a revised query.

Abstract: Multidimensional search capabilities are enabled on a non-PC (personal computer) device being utilized by a user. An original query submitted by the user via the non-PC device is received. A structured data repository is accessed to extract structured data that is available for the original query, where the extracted structured data represents attributes of the original query. The extracted structured data is provided to the user in the form of a hierarchical menu which allows the user to interactively modify the original query, such modification resulting in a revised query.

Abstract: Multidimensional search capabilities are enabled on a non-PC (personal computer) device being utilized by a user. An original query submitted by the user via the non-PC device is received. A structured data repository is accessed to extract structured data that is available for the original query, where the extracted structured data represents attributes of the original query. The extracted structured data is provided to the user in the form of a hierarchical menu which allows the user to interactively modify the original query, such modification resulting in a revised query.

Abstract: A media server in a Universal Plug and Play (UPnP) network includes a resource sharing service to govern the distribution of resource information regarding resources to rendering devices. In one case, the resource sharing service consults a criterion to determine whether an identified network device is authorized to receive resource information. In another case, the resource sharing service consults another criterion to determine whether a specified individual associated with the media server must consent to the transfer of the resource information in order for the transfer to occur. The resource information may include resource metadata that describes high level information regarding resources, as well as resource content. The media server includes various user interface presentations that allow the media server user to specify shared resources and distribution criteria.

Abstract: A UPnP network provides a flexible technique for retrieving a resource content item from a media server using a parameterized uniform resource locator (URL). In operation, the media server sends a control point a parameterized URL in response to a consumer's browse or search request. The URL includes at least one parameter that specifies a characteristic attribute of the resource content item, which determines the manner in which the resource content item can be presented. For example, the parameter can describe a format type of the resource content item, a format resolution of the resource content item, and/or other property of the resource content item. The control point can modify a value associated with the parameter to produce a modified URL. This modified URL is submitted to the media server, whereupon the media server locates the resource content item and converts it to the characteristic state specified by the modified URL (if conversion is needed).

Abstract: A network architecture in a Universal Plug and Play (UPnP) network includes a resource sharing service to govern the distribution of resource information from a server to a recipient entity (such as rendering device or a control point).

Abstract: A media server in a Universal Plug and Play (UPnP) network includes a resource sharing service to govern the distribution of media resource information to rendering devices. The media server includes: a media service module operating in a clamped down user context (e.g., a local service user context) and configured to share resource information over the network; a supplemental module operating in a local system user context and configured to assist the media service module in sharing resource information over the network; and a control panel module operating in a logged on user context and configured to interact with a user via a user interface display. The local system user context provides a higher level of access to media server resources compared to the clamped down user context. The media server also provides fast user switching (FUS) functionality that allows multiple users to have respective instances of the control panel module pending at the same time.