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 provides visual analysis of datasets. The method is performed at a computer system. A user selects a data source. In response, the system presents a natural language interface for analysis of data in the data source and presents a map data visualization within the graphical user interface for selecting geospatial data points from the data source. In response to receiving a first user input to select a first set of one or more geographic regions, the system calculates the similarity between the first set of one or more geographic regions and a second set of one or more geographic regions, based on a range of socio-economic, demographic, and/or geographic data fields from the data source, using one or more statistical techniques (e.g., Jensen-Shannon Divergence (JSD)). The system then updates and displays the map data visualization according to the calculated similarity.

Abstract: A method provides visual analysis of datasets. A user selects a data source. In response, the system presents a natural language interface for analysis of data in the data source and presents a map widget for selecting geospatial data points from the data source. A user provides a first user input to specify an incomplete natural language command directed to the data source and provides a second user input to select a region in the map widget. In response to the first user input and the second user input, the system generates and displays a map data visualization according to the first user input and the second user input, including a linguistic description of data points in the selected region. The system continues to display the selected region in the map widget. The map widget is configured to update the data visualization according to user modification of the selected region.

Abstract: A method provides visual analysis of datasets. The method is performed at a computer system. A user selects a data source. In response, the system presents a natural language interface for analysis of data in the data source and presents a map data visualization within the graphical user interface for selecting geospatial data points from the data source. In response to receiving a first user input to select a first set of one or more geographic regions, the system calculates the similarity between the first set of one or more geographic regions and a second set of one or more geographic regions, based on a range of socio-economic, demographic, and/or geographic data fields from the data source, using one or more statistical techniques (e.g., Jensen-Shannon Divergence (JSD)). The system then updates and displays the map data visualization according to the calculated similarity.

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.

Abstract: A method uses natural language for visual analysis of a dataset. The method displays a data visualization based on a first dataset. The method then extracts analytic phrases from a first natural language command related to the data visualization. The method computes conversation centers associated with the first natural language command based on the analytic phrases and computes analytical functions for the conversation centers, thereby creating functional phrases. The method updates the data visualization based on the functional phrases. The method extracts new analytic phrases from a second natural language command related to the updated data visualization and computes a temporary conversation centers associated with the second natural language command based on the new analytic phrases. The method derives new conversation centers from the original conversation centers and the temporary conversation centers using transitional rules.

Abstract: A method uses natural language for visual analysis of a dataset. A data visualization is displayed based on a first dataset. The method then extracts analytic phrases from a natural language command related to the data visualization. The method computes conversation centers based on the analytic phrases and computes analytical functions associated with the conversation centers, thereby creating functional phrases. The method updates the data visualization according to the functional phrases. The method then extracts analytic phrases from a second natural language command related to the updated data visualization, and computes temporary conversation centers from these analytic phrases. The method then computes cohesion between the first analytic phrases and the second analytic phrases to build a set of conversation centers, and computes analytical functions from this set of conversation centers, thereby creating functional phrases.

Abstract: A method uses natural language processing for visual analysis of a dataset by a computer. The computer displays a data visualization based on a dataset retrieved from a database using a set of one or more queries. The computer receives user input (e.g., keyboard or voice) to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization, the computer extracts one or more independent analytic phrases from the natural language command. The computer further computes semantic relatedness of extracted analytic phrases, and computes analytical functions associated with the extracted analytic phrases, thereby creating functional phrases. The computer requeries the database using an updated set of one or more queries based on the created functional phrases, thereby retrieving an updated dataset. The computer then displays an updated data visualization using the updated dataset.

Abstract: A method uses natural language processing for visual analysis of a dataset by a computer. The computer displays a data visualization based on a dataset retrieved from a database using a first set of database queries. The computer receives user input (e.g., keyboard or voice) to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization, the computer extracts one or more independent analytic phrases from the natural language command. The computer further computes a set of conversation centers associated with the natural language command based on the set of one or more analytic phrases. The computer then computes a set of analytical functions associated with the set of one or more conversation centers, thereby creating a set of one or more functional phrases. The device then updates the data visualization based on the set of one or more functional phrases.

Abstract: A method of using natural language processing for visual analysis of a data set includes displaying a data visualization based on a dataset retrieved from a database using a set of one or more queries and receiving a user input to specify a natural language command related to the displayed data visualization. The method further includes, based on the displayed data visualization, extracting one or more independent analytic phrases from the natural language command. The method further includes requerying the database using an updated set of one or more queries based on the extracted analytic phrases, thereby retrieving an updated dataset and displaying an updated data visualization using the updated dataset.