Abstract:
Disclosed herein are systems and methods for implementing a RELATED command with a predictive query interface including means for generating indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database of a host organization; exposing the database of the host organization via a request interface; receiving, at the request interface, a query for the database specifying a RELATED command term and a specified column as a parameter for the RELATED command term; querying the database using the RELATED command term and passing the specified column to generate a predictive record set; and returning the predictive record set responsive to the query, the predictive record set having a plurality of elements therein, each of the returned elements including a column identifier and a confidence indicator for the specified column passed with the RELATED command term, wherein the confidence indicator indicates whether a latent relationship exists between the specified column passed with the RELATED command and the column identifier returned for the respective element. Other related embodiments are further disclosed.
Abstract:
Disclosed herein are systems and methods for implementing a RELATED command with a predictive query interface including means for generating indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database of a host organization; exposing the database of the host organization via a request interface; receiving, at the request interface, a query for the database specifying a RELATED command term and a specified column as a parameter for the RELATED command term; querying the database using the RELATED command term and passing the specified column to generate a predictive record set; and returning the predictive record set responsive to the query, the predictive record set having a plurality of elements therein, each of the returned elements including a column identifier and a confidence indicator for the specified column passed with the RELATED command term, wherein the confidence indicator indicates whether a latent relationship exists between the specified column passed with the RELATED command and the column identifier returned for the respective element. Other related embodiments are further disclosed.
Abstract:
Disclosed herein are systems and methods for populating a table having null values using a predictive query interface including means for receiving a tabular dataset from a user as input, the tabular dataset having data values organized as columns and rows; identifying a plurality of null values within the tabular dataset, the null values being dispersed across multiple rows and multiple columns of the tabular dataset; generating indices from the tabular dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the tabular dataset; displaying the tabular dataset as output to the user, the displayed output including the data values depicted as known values and the null values depicted as unknown values; receiving input from the user to populate at least a portion of the unknown values within the displayed tabular dataset with predicted values; querying the indices for the predicted values; and displaying the predicted values as updated output to the user. Other related embodiments are further disclosed.
Abstract:
Disclosed herein are systems and methods for populating a table having null values using a predictive query interface including means for receiving a tabular dataset from a user as input, the tabular dataset having data values organized as columns and rows; identifying a plurality of null values within the tabular dataset, the null values being dispersed across multiple rows and multiple columns of the tabular dataset; generating indices from the tabular dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the tabular dataset; displaying the tabular dataset as output to the user, the displayed output including the data values depicted as known values and the null values depicted as unknown values; receiving input from the user to populate at least a portion of the unknown values within the displayed tabular dataset with predicted values; querying the indices for the predicted values; and displaying the predicted values as updated output to the user. Other related embodiments are further disclosed
Abstract:
Disclosed herein are systems and methods for implementing data upload, processing, and predictive query API exposure including means for receiving a dataset in a tabular form, the dataset having a plurality of rows and a plurality of columns; processing the dataset to generate indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices in a database; exposing an Application Programming Interface (API) to query the indices in the database; receiving a request for a predictive query or a latent structure query against the indices in the database; querying the database for a prediction based on the request via the API; and returning the prediction responsive to the request. Other related embodiments are further disclosed.
Abstract:
Disclosed herein are systems and methods for implementing data upload, processing, and predictive query API exposure including means for receiving a dataset in a tabular form, the dataset having a plurality of rows and a plurality of columns; processing the dataset to generate indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices in a database; exposing an Application Programming Interface (API) to query the indices in the database; receiving a request for a predictive query or a latent structure query against the indices in the database; querying the database for a prediction based on the request via the API; and returning the prediction responsive to the request. Other related embodiments are further disclosed.