Abstract: A method uses natural language for visual analysis of a dataset. A data visualization application displays a data visualization, at a computer, based on a dataset retrieved from a database using a set of one or more queries. A user specifies a natural language command related to the displayed data visualization, and the computer extracts an analytic phrase from the natural language command. The computer computes semantic relatedness between the analytic phrase and numeric data fields in the dataset. The computer identifies numeric data fields having highest semantic relatedness to the analytic phrase, and also selects a relevant numerical function. The numerical function compares data values in the numeric data fields to a threshold value. The computer retrieves an updated dataset that filters the identified numeric data fields according to the numeric function. The computer then displays an updated data visualization using the updated dataset.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: A method uses natural language for visual analysis of a dataset. A data visualization application displays a data visualization, at a computer, based on a dataset retrieved from a database using a set of one or more queries. A user specifies a natural language command related to the displayed data visualization, and the computer extracts an analytic phrase from the natural language command. The computer computes semantic relatedness between the analytic phrase and numeric data fields in the dataset. The computer identifies numeric data fields having highest semantic relatedness to the analytic phrase, and also selects a relevant numerical function. The numerical function compares data values in the numeric data fields to a threshold value. The computer retrieves an updated dataset that filters the identified numeric data fields according to the numeric function. The computer then displays an updated data visualization using the updated dataset.