Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: A method, system and computer readable program product are disclosed for compiling a spreadsheet to execute stream processing in a computing system. In an embodiment, the method comprises extracting a function from the spreadsheet, said function supporting data windows and stream partitioning in the computing system; and identifying input cells of the spreadsheet for holding input values for the function, and identifying output cells of the spreadsheet for holding output values of the function. In embodiments of the invention, a data stream is partitioned into a plurality of data stream partitions, and the extracted function is applied to the stream partitions in parallel. In embodiments of the invention, the extracted function is applied to the data stream partitions in series. The windows may be time based windows, and may be count based windows, and the windows may have variable sizes.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialogue with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialogue with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialog with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: A computer-implemented conversational agent engages in a natural language conversation with a user, interpreting the natural language conversation by parsing and tokenizing utterances in the natural language conversation. Based on interpreting, a set of utterances in the natural language conversation to be recorded as a macro is determined. The macro is stored in a database with an associated macro identifier. Replaying of the macro executes a function specified in the set of utterances.

Abstract: A method, system and computer readable program product are disclosed for encoding a function in a spreadsheet program to execute stream processing on a computing system. In embodiments of the invention, the method comprises encoding one or more formulas in one or more cells of the spreadsheet program, each of the formulas supporting data windows and stream partitioning; designating a first group of cells of the spreadsheet program as input cells for holding input values for the one or more formulas; and designating a second group of cells of the spreadsheet program as output cells for holding output values of the one or more formulas. In embodiments of the invention, the stream partitioning includes partitioning a defined stream of data into a plurality of data stream partitions, and the one or more formulas are encoded to operate on the plurality of data stream partitions.

Abstract: Automatic generation of a chat bot from an API specification to carry out a dialogue with a user and invoke an API call described in the API specification. Based on input API specification, a conversational bot specification representing a dialog flow is constructed. A natural language expression is received and transformed into instructions based on the conversational bot specification. Based on the instructions, a natural language prompt to the user and executable computer code for invoking the API call may be generated.

Abstract: Converting data transformations entered in a spreadsheet program into a circuit representation of those transformations. The circuit representation can run independently of the spreadsheet program to transform input data into output data. In some cases the circuit representation is in the form of hardware, accepts and/or produces data streams, and/or the circuit and/or output data or data streams can be shared among multiple users and/or subscribers. Where data streams are processed, the transformations may include well-specified timing semantics, supporting operations that involve rate-based rate manipulation, value-based rate manipulation, and/or access to past cell values.

Abstract: An entity grammar that specifies a computer conversational agent may be received. User utterances are interpreted based on the entity grammar and prompts for the conversational agent to pose are determined based on the entity grammar. An outcome of the dialog is built by storing words in the user utterances and the prompts that match tokens in the entity grammar. The entity grammar specifies both a dialog flow and data structure of the outcome.

Abstract: A method, system and computer readable program product are disclosed for encoding a function in a spreadsheet program to execute stream processing on a computing system. In embodiments of the invention, the method comprises encoding one or more formulas in one or more cells of the spreadsheet program, each of the formulas supporting data windows and stream partitioning; designating a first group of cells of the spreadsheet program as input cells for holding input values for the one or more formulas; and designating a second group of cells of the spreadsheet program as output cells for holding output values of the one or more formulas. In embodiments of the invention, the stream partitioning includes partitioning a defined stream of data into a plurality of data stream partitions, and the one or more formulas are encoded to operate on the plurality of data stream partitions.

Abstract: A method, system and computer readable program product are disclosed for compiling a spreadsheet to execute stream processing in a computing system. In an embodiment, the method comprises extracting a function from the spreadsheet, said function supporting data windows and stream partitioning in the computing system; and identifying input cells of the spreadsheet for holding input values for the function, and identifying output cells of the spreadsheet for holding output values of the function. In embodiments of the invention, a data stream is partitioned into a plurality of data stream partitions, and the extracted function is applied to the stream partitions in parallel. In embodiments of the invention, the extracted function is applied to the data stream partitions in series. The windows may be time based windows, and may be count based windows, and the windows may have variable sizes.

Abstract: Converting data transformations entered in a spreadsheet program into a circuit representation of those transformations. The circuit representation can run independently of the spreadsheet program to transform input data into output data. In some cases the circuit representation is in the form of hardware, accepts and/or produces data streams, and/or the circuit and/or output data or data streams can be shared among multiple users and/or subscribers. Where data streams are processed, the transformations may include well-specified timing semantics, supporting operations that involve rate-based rate manipulation, value-based rate manipulation, and/or access to past cell values.

Abstract: Converting data transformations entered in a spreadsheet program into a circuit representation of those transformations. The circuit representation can run independently of the spreadsheet program to transform input data into output data. In some cases the circuit representation is in the form of hardware, accepts and/or produces data streams, and/or the circuit and/or output data or data streams can be shared among multiple users and/or subscribers. Where data streams are processed, the transformations may include well-specified timing semantics, supporting operations that involve rate-based rate manipulation, value-based rate manipulation, and/or access to past cell values.

Abstract: Converting data transformations entered in a spreadsheet program into a circuit representation of those transformations. The circuit representation can run independently of the spreadsheet program to transform input data into output data. In some cases the circuit representation is in the form of hardware, accepts and/or produces data streams, and/or the circuit and/or output data or data streams can be shared among multiple users and/or subscribers. Where data streams are processed, the transformations may include well-specified timing semantics, supporting operations that involve rate-based rate manipulation, value-based rate manipulation, and/or access to past cell values.