Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: A computer-implemented technique is described herein for expediting a user's interaction with a digital assistant. In one implementation, the technique involves receiving a system prompt generated by a digital assistant in response to an input command provided by a user via an input device. The technique then generates a predicted response based on linguistic content of the system prompt, together with contextual features pertaining to a circumstance in which the system prompt was issued. The predicted response corresponds to a prediction of how the user will respond to the system prompt. The technique then selects one or more dialogue actions from a plurality of dialogue actions, based on a confidence value associated with the predicted response. The technique expedites the user's interaction with the digital assistant by reducing the number of system prompts that the user is asked to respond to.

Abstract: A user uploads date sets through a client to a database. The data sets are provisioned in the database for in-database searching. The data sets are evaluated and classifications for the columns of the tables that include the data set are detected. Columns content may be classified into different analysis types, aggregation types, formats, categories, hierarchies, etc. Metadata is generated based on the evaluation of the data sets. A schema is used to store the metadata that describes the detected classification of the columns. The schema is stored in the database and is used when a search in the database is performed.

Abstract: Methods, computer-readable media, and systems for managing business objects data sources. A search query that includes multiple query terms is received. Each query term at least partially represents metadata associated with one of multiple business objects data sources that each stores multiple data items. Multiple search index documents are searched to identify one or more business objects data sources that are each associated with metadata at least partially represented by each query term. Multiple metadata tables are searched to identify metadata associated with each identified business objects data source. The identified business objects data sources are searched for data items that satisfy the identified metadata. Representations of the data items and the metadata are provided in response to receiving the search query.

Abstract: Methods, non-transitory computer-readable media, and systems for managing business objects data sources. Multiple business objects data sources, each storing multiple data items, are accessed. For each data source, multiple computer-searchable index documents and multiple metadata tables, including master tables and mapping tables, are generated. The multiple computer-searchable index documents and the multiple metadata tables are provided to perform a search for data items in the multiple business objects data sources.

Abstract: A user uploads date sets through a client to a database. The data sets are provisioned in the database for in-database searching. The data sets are evaluated and classifications for the columns of the tables that include the data set are detected. Columns content may be classified into different analysis types, aggregation types, formats, categories, hierarchies, etc. Metadata is generated based on the evaluation of the data sets. A schema is used to store the metadata that describes the detected classification of the columns. The schema is stored in the database and is used when a search in the database is performed.

Abstract: Methods, computer-readable media, and systems for managing business objects data sources. A search query that includes multiple query terms is received. Each query term at least partially represents metadata associated with one of multiple business objects data sources that each stores multiple data items. Multiple search index documents are searched to identify one or more business objects data sources that are each associated with metadata at least partially represented by each query term. Multiple metadata tables are searched to identify metadata associated with each identified business objects data source. The identified business objects data sources are searched for data items that satisfy the identified metadata. Representations of the data items and the metadata are provided in response to receiving the search query.

Abstract: Methods, non-transitory computer-readable media, and systems for managing business objects data sources. Multiple business objects data sources, each storing multiple data items, are accessed. For each data source, multiple computer-searchable index documents and multiple metadata tables, including master tables and mapping tables, are generated. The multiple computer-searchable index documents and the multiple metadata tables are provided to perform a search for data items in the multiple business objects data sources.