Abstract: In non-limiting examples of the present disclosure, systems, methods, and devices for enabling conversational bot communications are presented. A marketplace comprising an identity of a plurality of skills may be maintained, each of the plurality of skills associated with a manifest and a conversational bot. A request for execution of a specific skill may be received. A plurality of conversational bots may be identified, each of the plurality of conversational bots being associated with a manifest for executing the specific skill. The plurality of conversational bots may be ranked. The specific skill may be caused to be executed by the highest ranked conversational bot. In some examples, a plurality of highest ranked conversational bots may be surfaced and a bot that is selected may execute the specific skill.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A marketplace comprising an identity of a plurality of skills may be maintained, each of the plurality of skills associated with a manifest and a conversational bot. A request for execution of a specific skill may be received. A plurality of conversational bots may be identified, each of the plurality of conversational bots being associated with a manifest for executing the specific skill. The plurality of conversational bots may be ranked. The specific skill may be caused to be executed by the highest ranked conversational bot. In some examples, a plurality of highest ranked conversational bots may be surfaced and a bot that is selected may execute the specific skill.

Abstract: The present disclosure relates to processing operations configured to generate and present a chat bot diagnostic visualization that provides real-time visual insights into operation of a chat bot for debugging assistance. A chat bot diagnostic tool is programmed to launch a graphical user interface that displays a visual representation of diagnostic data for debugging a chat bot in real-time. To enable conversational specific data to be reviewed, the present disclosure is configured to implement a middleware adapter within in a run-time stack of a chat bot that is configured to trace data traffic between a chat bot and a channel of an application/service. This enables the chat bot diagnostic tool to observe data traffic and filter the data traffic to identify relevant data for debugging a chat bot. A debugging data visualization of a chat bot interaction is emulated through a graphical user interface of the chat bot diagnostic tool.

Abstract: A natural language model can be primed utilizing optimized examples generated from a labeled knowledge graph corresponding to an independently developed application program. Parsing of the labeled knowledge graph can include the identification of triples, comprising a source node, a destination node, and a link between them, each of which can be labeled. One or more natural language input examples can be generated from an individual triple by concatenating the natural language words or phrases utilized to label the source node in the link. Determinations that subsequently received natural language user input is similar to the generated examples can result in an identification of the triple, which can, in turn, trigger the performance of a function associated with the destination node of the triple. Labels can include preferred labels and alternative labels, and various permutations thereof can be concatenated to generate alternative natural language input examples.

Abstract: A natural language model can be primed utilizing optimized examples generated from a labeled knowledge graph corresponding to an independently developed application program. Parsing of the labeled knowledge graph can include the identification of triples, comprising a source node, a destination node, and a link between them, each of which can be labeled. One or more natural language input examples can be generated from an individual triple by concatenating the natural language words or phrases utilized to label the source node in the link. Determinations that subsequently received natural language user input is similar to the generated examples can result in an identification of the triple, which can, in turn, trigger the performance of a function associated with the destination node of the triple. Labels can include preferred labels and alternative labels, and various permutations thereof can be concatenated to generate alternative natural language input examples.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A natural language input may be received by a first conversational bot. A skill needed to fulfill a request in the natural language input may be identified. A determination may be made that the skill is not executable by the first conversational bot. A determination may be made that the skill is executable by a second conversational bot. A request for execution of the skill may be sent from the first conversational bot to the second conversational bot. A request for information needed for the second conversational bot to execute the skill may be received by the first conversational bot from the second conversational bot. The information may be sent from the first conversational bot to the second conversational bot. The skill may be executed.

Abstract: A natural language model can be primed utilizing optimized examples generated from a labeled knowledge graph corresponding to an independently developed application program. Parsing of the labeled knowledge graph can include the identification of triples, comprising a source node, a destination node, and a link between them, each of which can be labeled. One or more natural language input examples can be generated from an individual triple by concatenating the natural language words or phrases utilized to label the source node in the link. Determinations that subsequently received natural language user input is similar to the generated examples can result in an identification of the triple, which can, in turn, trigger the performance of a function associated with the destination node of the triple. Labels can include preferred labels and alternative labels, and various permutations thereof can be concatenated to generate alternative natural language input examples.

Abstract: Systems and methods are provided for storing and retrieving data using a linked data model having a tree format. Instead of using a traditional relational database, a linked data model can be used with links between data items that reflect the underlying business logic. To facilitate retrieval of data, the data items stored using the linked data model can be individually addressable.

Abstract: A system and method of automating data profile updating and querying includes building bots using standard schema having predefined data types for collecting data relating to a user or object. A bot stores the collected data in a data profile for the user or object in a graph data store that is queried by that bot or another bot to extract data relating to the user or object. The data relating to the user or object may be collected from two or more data channels including, for example, a channel of spoken data and a channel of typed data. The collected data is selectively processed by a bot to establish context for the collected data and is inserted into a knowledge graph that may be joined to another knowledge graph for querying. The bots automate the collection and sharing of collected profile data with other bots in an application ecosystem.

Abstract: A natural language model can be primed utilizing optimized examples generated from a labeled knowledge graph corresponding to an independently developed application program. Parsing of the labeled knowledge graph can include the identification of triples, comprising a source node, a destination node, and a link between them, each of which can be labeled. One or more natural language input examples can be generated from an individual triple by concatenating the natural language words or phrases utilized to label the source node in the link. Determinations that subsequently received natural language user input is similar to the generated examples can result in an identification of the triple, which can, in turn, trigger the performance of a function associated with the destination node of the triple. Labels can include preferred labels and alternative labels, and various permutations thereof can be concatenated to generate alternative natural language input examples.

Abstract: A natural language model can be primed utilizing optimized examples generated from a labeled knowledge graph corresponding to an independently developed application program. Parsing of the labeled knowledge graph can include the identification of triples, comprising a source node, a destination node, and a link between them, each of which can be labeled. One or more natural language input examples can be generated from an individual triple by concatenating the natural language words or phrases utilized to label the source node in the link. Determinations that subsequently received natural language user input is similar to the generated examples can result in an identification of the triple, which can, in turn, trigger the performance of a function associated with the destination node of the triple. Labels can include preferred labels and alternative labels, and various permutations thereof can be concatenated to generate alternative natural language input examples.

Abstract: At least some embodiments described herein relate to computer-assisted conversation. The set of available conversation segments is updated by addressing conversation segments at the granularity of a conversation segment or a group of conversation segments. For instance, an entire class of conversation segments may be addressed to add, delete, turn on, or turn off, the class of conversation segments. Groups of class of conversation segments may also be similarly addressed. Thus, as the scope of a conversation changes, the available set of conversation segments may likewise change with fine-grained control. Accordingly, rather than pre-plan every set of possible conversations, the context and direction of the conversation may be evaluated by code to thereby determine what new sets of conversation segments should be added, deleted, turned on, or turned off. New conversation segments may even be generated dynamically, taking into account the values of parameters that then exist.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A marketplace comprising an identity of a plurality of skills may be maintained, each of the plurality of skills associated with a manifest and a conversational bot. A request for execution of a specific skill may be received. A plurality of conversational bots may be identified, each of the plurality of conversational bots being associated with a manifest for executing the specific skill. The plurality of conversational bots may be ranked. The specific skill may be caused to be executed by the highest ranked conversational bot. In some examples, a plurality of highest ranked conversational bots may be surfaced and a bot that is selected may execute the specific skill.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A natural language input may be received by a first conversational bot. A skill needed to fulfill a request in the natural language input may be identified. A determination may be made that the skill is not executable by the first conversational bot. A determination may be made that the skill is executable by a second conversational bot. A request for execution of the skill may be sent from the first conversational bot to the second conversational bot. A request for information needed for the second conversational bot to execute the skill may be received by the first conversational bot from the second conversational bot. The information may be sent from the first conversational bot to the second conversational bot. The skill may be executed.

Abstract: Methods, systems, and computer program products for dispatching an incoming event are described. A scoring stack is accessed, the scoring stack comprising an identity of one or more tasks, each task corresponding to one or more scorable functions. A scorable tree is generated based on the one or more scorable functions corresponding to the one or more tasks of the scoring stack and the incoming event is processed using the scorable tree to generate one or more scores. One or more actions identified in the scorable tree are performed based on the one or more scores.

Abstract: The present disclosure relates to processing operations configured to generate and present a chat bot diagnostic visualization that provides real-time visual insights into operation of a chat bot for debugging assistance. A chat bot diagnostic tool is programmed to launch a graphical user interface that displays a visual representation of diagnostic data for debugging a chat bot in real-time. To enable conversational specific data to be reviewed, the present disclosure is configured to implement a middleware adapter within in a run-time stack of a chat bot that is configured to trace data traffic between a chat bot and a channel of an application/service. This enables the chat bot diagnostic tool to observe data traffic and filter the data traffic to identify relevant data for debugging a chat bot. A debugging data visualization of a chat bot interaction is emulated through a graphical user interface of the chat bot diagnostic tool.

Abstract: A system and method of automating data profile updating and querying includes building bots using standard schema having predefined data types for collecting data relating to a user or object. A bot stores the collected data in a data profile for the user or object in a graph data store that is queried by that bot or another bot to extract data relating to the user or object. The data relating to the user or object may be collected from two or more data channels including, for example, a channel of spoken data and a channel of typed data. The collected data is selectively processed by a bot to establish context for the collected data and is inserted into a knowledge graph that may be joined to another knowledge graph for querying. The bots automate the collection and sharing of collected profile data with other bots in an application ecosystem.

Abstract: At least some embodiments described herein relate to computer-assisted conversation. The set of available conversation segments is updated by addressing conversation segments at the granularity of a conversation segment or a group of conversation segments. For instance, an entire class of conversation segments may be addressed to add, delete, turn on, or turn off, the class of conversation segments. Groups of class of conversation segments may also be similarly addressed. Thus, as the scope of a conversation changes, the available set of conversation segments may likewise change with fine-grained control. Accordingly, rather than pre-plan every set of possible conversations, the context and direction of the conversation may be evaluated by code to thereby determine what new sets of conversation segments should be added, deleted, turned on, or turned off. New conversation segments may even be generated dynamically, taking into account the values of parameters that then exist.

Abstract: At least some embodiments described herein relate to computer-assisted conversation. The set of available conversation segments is updated by addressing conversation segments at the granularity of a conversation segment or a group of conversation segments. For instance, an entire class of conversation segments may be addressed to add, delete, turn on, or turn off, the class of conversation segments. Groups of class of conversation segments may also be similarly addressed. Thus, as the scope of a conversation changes, the available set of conversation segments may likewise change with fine-grained control. Accordingly, rather than pre-plan every set of possible conversations, the context and direction of the conversation may be evaluated by code to thereby determine what new sets of conversation segments should be added, deleted, turned on, or turned off. New conversation segments may even be generated dynamically, taking into account the values of parameters that then exist.

Abstract: Systems and methods are provided for storing and retrieving data using a linked data model having a tree format. Instead of using a traditional relational database, a linked data model can be used with links between data items that reflect the underlying business logic. To facilitate retrieval of data, the data items stored using the linked data model can be individually addressable.