Systems, methods, and apparatuses for implementing a group command with a predictive query interface

• US 9,349,132 B2
• Filed: 08/29/2013
• Issued: 05/24/2016
• Est. Priority Date: 03/13/2013
• Status: Active Grant

• Current Assignee: Salesforce.com, Inc.
• Original Assignee: Salesforce.com, Inc.
• Inventors: Cronin, Beau David, Obermeyer, Fritz Heinrich, Jonas, Eric Michael, Glidden, Jonathan
• Primary Examiner(s): Truong, Cam-Y
• Application Number:
  US14/014,250
• Publication Number:
  US 20140280153A1
• Time in Patent Office: 999 Days
• Field of Search: 707/737
• US Class Current: 1/1
• CPC Class Codes: G06F 16/20 of structured data, e.g. relational data
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/2282 Tablespace storage structures; Management thereof
• CPC Class Codes: G06F 16/23 Updating
• CPC Class Codes: G06F 16/244 Grouping and aggregation
• CPC Class Codes: G06F 16/2445 Data retrieval commands; View definitions
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/24553 of query operations
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 16/24558 Binary matching operations
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2458 Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/2471 Distributed queries
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/316 Indexing structures
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 3/04842 : Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04847 : Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 40/18 : of spreadsheets form-filling G06F40/174
• CPC Class Codes: G06N 20/00 : Machine learning
• CPC Class Codes: G06N 7/01 : Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 30/0201 : Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 : Market predictions or forecasting for commercial activities

Abstract

Disclosed herein are systems and methods for implementing a GROUP 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 GROUP command term and a specified column as a parameter for the GROUP command term; querying the database using the GROUP 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 groups specified therein, each of the returned groups of the predictive record set including a group of one or more rows of the dataset. Other related embodiments are further disclosed.

Claims

1. A method in a system of a host organization, the system having at least a processor and a memory therein, wherein the method comprises:

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 system of the host organization;

exposing the database system of the host organization via a request interface;

receiving, at the request interface, a query for the database system specifying a GROUP command term and a specified column as a parameter for the GROUP command term;

querying the database system using the GROUP command term and passing the specified column to generate a predictive record set;

returning the predictive record set responsive to the query, the predictive record set having a plurality of groups specified therein, each returned group of the returned groups of the predictive record set including a group of one or more rows of the dataset; and

wherein a confidence indicator returned with each respective row of the one or more rows specified within each group of the plurality of groups returned with the predictive record set ranges from a minimum of 0 indicating a lowest possible confidence in a result that the respective row belongs to the group specified to a maximum of 1 indicating a highest possible confidence in the result that the respective row belongs to the group specified.

2. The method of claim 1, wherein all of the rows of the dataset are partitioned by assigning every row of the dataset to exactly one of the plurality of groups returned with the predictive record set without overlap of any single row being assigned to more than one of the plurality of groups.

3. The method of claim 1:

wherein the rows of the dataset are segmented by assigning rows of the dataset to at most one of the plurality of groups without overlap of any single row being assigned to more than one of the plurality of groups; and

wherein segmentation results in one or more rows of the dataset remaining unassigned to any of the plurality of groups due to the confidence indicator for corresponding one or more rows remaining unassigned falling below a minimum threshold.

4. The method of claim 1, wherein the column passed with the GROUP command term provides the context of a latent structure in which the one or more rows of each specified group are assessed for similarity to any other rows within the same group, wherein the column passed with the GROUP command term provides the context of a latent structure in which the one or more rows of each specified group are assessed for similarity to any other rows within the same group.

5. The method of claim 1, wherein the predictive record set having a plurality of groups specified therein comprises a listing of row identifiers from the dataset or the indices and a corresponding confidence indicator for each row identifier of the row identifiers specified.

6. The method of claim 1, wherein each row corresponds to a registered voter and wherein the groupings specified by the predictive record define naturally targetable voting blocs with each voting bloc predicted to be likely to react similarly to one or more of a common campaign message, a common campaign issue, and common campaign advertising.

7. The method of claim 1, wherein each row corresponds to an economic market participant and wherein the groupings specified by the predictive record set define naturally targetable advertising groups with economic market participants of each advertising group predicted to react similarly to a common advertising campaign directed thereto.

8. The method of claim 1, further comprising:

indicating a most representative row within each respective group of the respective groups returned with the predictive record set, wherein the most representative row for each group of the groups returned corresponds to an actual row of the dataset.

9. The method of claim 1, further comprising:

indicating a most stereotypical row within each respective group of the respective groups returned with the predictive record set, wherein the most stereotypical row does not exist as a row of the dataset, the most stereotypical row having synthesized data based on actual rows within the dataset for the specified group to which the most stereotypical row corresponds.

10. The method of claim 1, further comprising:

passing a minimum confidence threshold with the GROUP command term; and

wherein returning the predictive record set comprises returning only rows of the groups in the predictive record set having the confidence indicator in excess of the minimum confidence threshold.

11. The method of claim 1, wherein exposing the database system of the host organization comprises exposing a Predictive Query Language Application Programming Interface (PreQL API) directly to authenticated users, wherein the PreQL API is accessible to the authenticated users via a public Internet.

12. The method of claim 11, wherein querying the database system using the GROUP command term comprises passing a PreQL query to the database system, the PreQL query having a query syntax of:

the GROUP command term as a required term;

a COLUMN term as a required term, the COLUMN term specifying the column to be passed with the GROUP command term;

an optional FROM term specifying one or more tables, datasets, data sources, or indices, or any combination thereof, to be queried when the optional FROM term is specified; and

wherein a default value is used when the optional FROM term is not specified.

13. The method of claim 12, wherein the query syntax for the PreQL query further provides:

an optional CONFIDENCE term that, when provided, specifies a minimum acceptable threshold for respective confidence indicators corresponding to each row of the rows to be returned with the groups of the predictive record set.

14. The method of claim 12, wherein querying the database system using the GROUP command term comprises passing a JavaScript Object Notation (JSON) structured query to the database system, the JSON structured query having a query syntax of:

the GROUP command term as a required term;

an optional one or more tables, datasets, data sources, or indices to be queried or a default value for the one or more tables, datasets, data sources, or indices to be queried when not specified;

the column to be passed with the GROUP command term; and

an optional specification of a minimum acceptable confidence for the rows of the groups to be returned with the predictive record set according to the confidence indicator corresponding to each row of the rows.

15. The method of claim 1:

wherein exposing the database system of the host organization comprises exposing a web form directly to authenticated users, wherein the web form is accessible to the authenticated users via a public Internet;

wherein the host organization generates a latent structure query for submission to the database system based on input from the web form; and

wherein querying the database system using the GROUP command term comprises querying the database system using the latent structure query via a Predictive Query Language Application Programming Interface (PreQL API) within the host organization, the PreQL API being indirectly exposed to authenticated users through the web form.

16. The method of claim 1:

wherein querying the database system using the GROUP command term comprises executing a Predictive Query Language (PreQL) structured query against the database system for the GROUP command term; and

wherein the method further comprises executing one or more additional PreQL structured queries against the database system, each additional PreQL structured query of the one or more additional PreQL structured queries specifying at least one command selected from the group of PreQL commands comprising;

PREDICT and GROUP.

17. The method of claim 1, further comprising:

receiving the dataset from an authenticated subscriber and subsequently receiving the query for the database system from the authenticated subscriber; and

processing the dataset on behalf of the authenticated subscriber to generate the indices.

18. The method of claim 1:

wherein each row of the plurality of rows in the dataset corresponds to an entity;

wherein each column of the plurality of columns corresponds to a characteristic for entities; and

wherein a point of intersection between each respective row and each column of the plurality of columns forms a cell to store a value at the point of intersection.

19. A non-transitory computer readable storage medium having instructions stored thereon that, when executed by a processor in a host organization, the instructions cause the host organization to perform operations comprising:

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 the 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 GROUP command term and a specified column as a parameter for the GROUP command term;

querying the database using the GROUP command term and passing the specified column to generate a predictive record set;

returning the predictive record set responsive to the query, the predictive record set having a plurality of groups specified therein, each returned group of the returned groups of the predictive record set including a group of one or more rows of the dataset; and

wherein a confidence indicator returned with each respective row of the one or more rows specified within each group of the plurality of groups returned with the predictive record set ranges from a minimum of 0 indicating a lowest possible confidence in a result that the respective row belongs to the group specified to a maximum of 1 indicating a highest possible confidence in the result that the respective row belongs to the group specified.

20. The non-transitory computer readable storage medium of claim 19, wherein querying the database using the GROUP command term comprises passing a PreQL query to the database, the PreQL query having a query syntax of:

the GROUP command term as a required term;

a COLUMN term as a required term, the COLUMN term specifying the column to be passed with the GROUP command term;

an optional FROM term specifying one or more tables, datasets, data sources, or indices, or any combination thereof, to be queried when the optional FROM term is specified;

wherein a default value is used when the optional FROM term is not specified;

and an optional CONFIDENCE term that, when provided, specifies a minimum acceptable threshold for respective confidence indicators corresponding to each row of the rows to be returned with the groups of the predictive record set.

21. The non-transitory computer readable storage medium of claim 19, wherein querying the database using the GROUP command term comprises passing a JavaScript Object Notation (JSON) structured query to the database, the JSON structured query having a query syntax of:

the GROUP command term as a required term;

an optional one or more tables, datasets, data sources, or indices to be queried or a default value for the one or more tables, datasets, data sources, or indices to be queried when not specified;

the column to be passed with the GROUP command term; and

an optional specification of a minimum acceptable confidence for the rows of the groups to be returned with the predictive record set according to the confidence indicator corresponding to each row of the rows.

22. A system to operate within a host organization, the system comprising:

a processor to execute instructions stored in memory of the system;

an analysis engine to generate indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset;

a predictive database to store the indices;

a request interface to expose the predictive database;

the request interface to receive a query for the predictive database specifying a GROUP command term and a specified column as a parameter for the GROUP command term;

a query interface to query the predictive database using the GROUP command term and passing the specified column to generate a predictive record set;

the request interface to further return the predictive record set responsive to the query, the predictive record set having a plurality of groups specified therein, each returned group of the returned groups of the predictive record set including a group of one or more rows of the dataset; and

wherein a confidence indicator returned with each respective row of the one or more rows specified within each group of the plurality of groups returned with the predictive record set ranges from a minimum of 0 indicating a lowest possible confidence in a result that the respective row belongs to the group specified to a maximum of 1 indicating a highest possible confidence in the result that the respective row belongs to the group specified.

23. The system of claim 22:

wherein the predictive database is to execute as an on-demand cloud based service at the host organization for one or more subscribers; and

wherein the system further comprises an authenticator to verify client devices are associated with a subscriber and to further verify authentication credentials for the respective subscriber.

24. The system of claim 22, wherein the request interface exposes a Predictive Query Language Application Programming Interface (PreQL API) directly to authenticated users, wherein the PreQL API is accessible to the authenticated users via a public Internet.

25. The system of claim 24, wherein the query interface is to pass a Predictive Query Language (PreQL) structured query to the predictive database to execute the query, the PreQL structured query having a query syntax of:

the GROUP command term as a required term;

a COLUMN term as a required term, the COLUMN term specifying the column to be passed with the GROUP command term;

an optional FROM term specifying one or more tables, datasets, data sources, or indices or any combination thereof, to be queried when the optional FROM term is specified;

wherein a default value is used when the optional FROM term is not specified; and

an optional CONFIDENCE term that, when provided, specifies a minimum acceptable threshold for respective confidence indicators corresponding to each row of the rows to be returned with the groups of the predictive record set.

26. The system of claim 22, further comprising:

a web-server to implement the request interface;

wherein the web-server is to receive as input, a plurality of access requests from one or more client devices from among a plurality of customer organizations communicably interfaced with the host organization via a network;

a multi-tenant database system with predictive database functionality to implement the predictive database; and

wherein each customer organization is an entity selected from the group consisting of;

a separate and distinct remote organization, an organizational group within the host organization, a business partner of the host organization, or a customer organization that subscribes to cloud computing services provided by the host organization.

27. The system of claim 22 wherein the rows of the dataset are segmented by assigning rows of the dataset to at most one of the plurality of groups without overlap of any single row being assigned to more than one of the plurality of groups;

and wherein segmentation results in one or more rows of the dataset remaining unassigned to any of the plurality of groups due to the confidence indicator for corresponding one or more rows remaining unassigned falling below a minimum threshold.