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:
The technology disclosed describes systems and methods for delivering software trial demonstrations that are customized, with features identified as interesting to a software demonstration candidate, by mining biographical and behavioral data of the candidate. The technology further discloses systems and methods for the customization of trial demonstrations with software usage stories that reflect a software demonstration candidate's interests, identified by analyzing mined biographical and behavioral data about the candidate.
Abstract:
In an example, a processing system of a database system may be configured to cause a user system that is coupled to the database system over a network to display a list of a plurality of factors from which the processing system derived a first value of a customer relationship management record. The processing system may be configured to determine whether a person selects a factor of the list. The processing system may be configured to deriving a second value that is different than the first value from at least a subset of the plurality of factors in response to determining that the person selects the factor from the list. The processing system may perform at least one of causing the second value to be displayed on the user system or retaining an association of the second value to the customer relationship management record.
Abstract:
The technology disclosed describes systems and methods for delivering software trial demonstrations that are customized, with features identified as interesting to a software demonstration candidate, by mining biographical and behavioral data of the candidate. The technology further discloses systems and methods for the customization of trial demonstrations with software usage stories that reflect a software demonstration candidate's interests, identified by analyzing mined biographical and behavioral data about the candidate.
Abstract:
The technology disclosed describes systems and methods for delivering software trial demonstrations that are customized, with features identified as interesting to a software demonstration candidate, by mining biographical and behavioral data of the candidate. The technology further discloses systems and methods for the customization of trial demonstrations with software usage stories that reflect a software demonstration candidate's interests, identified by analyzing mined biographical and behavioral data about the candidate.
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.