System to generate curated ontologies

• US 9,760,606 B1
• Filed: 11/29/2016
• Issued: 09/12/2017
• Est. Priority Date: 10/05/2016
• Status: Active Grant

• Current Assignee: Palantir Technologies Incorporated
• Original Assignee: Palantir Technologies Incorporated
• Inventors: Wilczynski, Peter, Beiermeister, Ryan, Slatcher, Timothy, Elder, Andrew
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US15/364,131
• Time in Patent Office: 287 Days
• Field of Search: 706 12
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/2322 using timestamps
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/252 between a Database Management System and a front-end application
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06F 16/289 Object oriented databases
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

Example embodiments relate to a network-based ontology curation system employed for receiving a request to view a data object, curating an ontology associated with the data object on-the-fly based on attributes of the request that include device and user characteristics.

Claims

1. A system comprising:

one or more processors of a machine; and

a memory storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising;

receiving a request for a data object from a requesting device, the request including one or more request attributes that include at least a device type of the requesting device;

accessing a database that includes a set of data objects associated with the data object in response to the receiving the request;

retrieving the set of data objects associated with the data object from the database;

prioritizing the set of data objects associated with the data object based on the one or more request attributes, including the device type of the requesting device; and

curating an ontology based on the prioritized set of data objects associated with the data object.

2. The system of claim 1, wherein the database is a primary database, and the operations further comprise:

receiving the set of data objects at the primary database, the set of data objects including the data object, an identifier of the data object, and a time-stamp of the data object;

parsing the set of data objects to retrieve the identifier and the time-stamp;

assigning a foreign key to the identifier and the timestamp, the foreign key indicating a location of the set of data objects within the primary database; and

indexing the foreign key, the identifier, and the time-stamp at a secondary database.

3. The system of claim 2, wherein the request includes the identifier of the data object, and the retrieving the set of data objects from the primary database includes:

retrieving the foreign key from the secondary database based on the identifier; and

retrieving the set of data objects from the primary database.

4. The system of claim 2, wherein the secondary database is a relational database.

5. The system of claim 1, wherein the request is a first request, the ontology is a first ontology, and the operations further comprise:

training a machine learned model based on the first request and the request attributes;

receiving a second request that includes the request attributes of the first request; and

prioritizing the set of data objects for the second request based on the machine learned model and the request attributes.

6. The system of claim 1, wherein the request is a first request, and the operations further comprise:

receiving a prioritization configuration associated with the request attributes of the request; and

wherein the prioritizing the set of data objects is based on the prioritization configuration and the request attributes.

7. The system of claim 1, wherein the operations further comprise:

generating a presentation of the data object based on the ontology; and

causing display of the presentation at the requesting device.

8. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:

receiving a request for a data object from a requesting device, the request including request attributes that include at least a device type of the requesting device;

accessing a database that includes a set of data objects associated with the data object in response to the receiving the request;

retrieving the set of data objects from the database;

prioritizing the set of data objects based on the request attributes, including the device type of the requesting device; and

curating an ontology based on the prioritized set of data objects associated with the data object.

9. The non-transitory machine-readable storage medium of claim 8, wherein the database is a primary database, and the operations further comprise:

receiving the set of data objects at the primary database, the set of data objects including at least the data object, an identifier of the data object, and a time-stamp of the data object;

parsing the set of data objects to retrieve the identifier and the time-stamp;

assigning a foreign key to the identifier and the timestamp, the foreign key indicating a location of the set of data objects within the primary database; and

indexing the foreign key, the identifier and the time-stamp at a secondary database.

10. The non-transitory machine-readable storage medium of claim 9, wherein the request includes the identifier of the data object, and the operations for the retrieving the set of data objects from the primary database further comprises:

retrieving the foreign key from the secondary database based on the identifier; and

retrieving the set of data objects from the primary database.

11. The non-transitory machine-readable storage medium of claim 9, wherein the secondary database is a relational database.

12. The non-transitory machine-readable storage medium of claim 8, wherein the request is a first request, the ontology is a first ontology, and the operations further comprise:

training a machine learned model based on the first request and the request attributes;

receiving a second request that includes the request attributes of the first request; and

prioritizing the set of data objects for the second request based on the machine learned model and the request attributes.

13. The non-transitory machine-readable storage medium of claim 8, wherein the request is a first request, and the operations further comprise:

receiving a prioritization configuration associated with the request attributes of the request; and

wherein the prioritizing the set of data objects is based on the prioritization configuration and the request attributes.

14. The non-transitory machine-readable storage medium of claim 8, wherein the operations further comprise:

generating a presentation of the data object based on the ontology; and

causing display of the presentation at the requesting device.

15. A method comprising:

receiving a request for a data object from a requesting device, the request including request attributes that include at least a device type of the requesting device;

accessing a database that includes a set of data objects associated with the data object in response to the receiving the request;

retrieving the set of data objects from the database;

prioritizing the set of data objects based on the request attributes, including the device type of the requesting device; and

curating an ontology based on the prioritized set of data objects associated with the data object.

16. The method of claim 15, wherein the database is a primary database, and the method further comprises:

receiving the set of data objects at the primary database, the set of data objects including at least the data object, an identifier of the data object, and a time stamp of the data object;

parsing the set of data objects to retrieve the identifier and the time stamp;

assigning a foreign key to the identifier and the time stamp, the foreign key indicating a location of the set of data objects within the primary database; and

indexing the foreign key, the identifier, and the time stamp at a secondary database.

17. The method of claim 16, wherein the request includes the identifier of the data object, and the receiving the set of data objects at the primary database includes:

retrieving the foreign key from the secondary database based on the identifier; and

retrieving the set of data objects from the primary database.

18. The method of claim 16, wherein the secondary database is a relational database.

19. The method of claim 15, wherein the request is a first request, the ontology is a first ontology, and the method further comprises:

training a machine-learning model based on the first request and the request attributes;

receiving a second request that includes the request attributes of the first request; and

prioritizing the set of data objects for the second request based on the machine-learning model and the request attributes.

20. The method of claim 15, wherein the request is a first request, and the method further comprises:

receiving a prioritization configuration associated with the request attributes of the request; and

wherein the prioritizing the set of data objects is based on the prioritization configuration and the request attributes.