Systems and user interfaces for data analysis including artificial intelligence algorithms for generating optimized packages of data items

• US 9,652,510 B1
• Filed: 04/12/2016
• Issued: 05/16/2017
• Est. Priority Date: 12/29/2015
• Status: Active Grant

• Current Assignee: Palantir Technologies Incorporated
• Original Assignee: Palantir Technologies Incorporated
• Inventors: Huang, Yifei, Garde, Grace, Singh, Nikhita, Gershkon, Sarah, Winchester, James, Pliuskys, Laurynas
• Primary Examiner(s): Alam, Shahid
• Application Number:
  US15/096,832
• Time in Patent Office: 399 Days
• Field of Search: 707723, 707737
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

Systems and user interfaces enable integration of data items from disparate sources to generate optimized packages of data items. For example, the systems described herein can obtain data items from various sources, score the data items, and present, via an interactive user interface, options for packaging the data items based on the scores. The systems may include artificial intelligence algorithms for selecting optimal combinations of data items for packaging. Further, the interactive user interfaces may enable a user to efficiently add data items to, and remove data items from, the data packages. The system may interactively re-calculate and update scores associated with the package of data items as the user interacts with the data package via the user interface. The systems and user interfaces may thus, according to various embodiments, enable the user to optimize the packages of data items based on multiple factors quickly and efficiently.

Claims

1. A system for enabling efficient packaging of data items based on and incorporating artificial intelligence recommendations, the system comprising:

one or more databases storing;

a plurality of data items; and

a package of data items, wherein the package of data items includes a subset of the plurality of data items, and wherein the package of data items is related to an entity;

a data store configured to store computer-executable instructions; and

a processor in communication with the data store, wherein the computer-executable instructions, when executed, cause the processor to;

analyze the subset of the plurality of data items to determine a package score;

execute an artificial intelligence algorithm to generate a plurality of recommendations by at least;

determining a historical trend related to the entity;

determining, for each data item of at least some of the plurality of data items, an effect on the package score if the data item were to be added to the package; and

determining, based at least in part on a combination of historical trend and the effects, a ranking of the at least some of the plurality of data items;

generate user interface data usable for rendering an interactive user interface, the interactive user interface including;

an indication of the package score,

a list of the subset of data items, and

a list of the plurality of recommendations ordered based on the ranking;

receive a selection of a recommendation from the plurality of recommendations;

add the data item associated with the recommendation to the package of data items such that the package of data items includes an updated subset of the plurality of data items including the data item;

analyze the updated subset of the plurality of data items to determine an updated package score; and

update the user interface data such that the interactive user interface further includes;

an indication of the updated package score, and

a list of the updated subset of data items.

2. The system of claim 1, wherein the computer-executable instructions, when executed, cause the processor to further:

execute the artificial intelligence algorithm to generate an updated plurality of recommendations by at least;

determining, for each data item of at least some of the plurality of data items, an updated effect on the updated package score if the data item were to be added to the package; and

determining, based on the updated effects, an updated ranking of the at least some of the plurality of data items; and

update the user interface data such that the interactive user interface further includes;

a list of the updated plurality of recommendations ordered based on the updated ranking.

3. The system of claim 2, wherein the plurality of recommendations include a portion of the at least some of the plurality of data items that are highly ranked, and wherein the updated plurality of recommendations include an updated portion of the at least some of the plurality of data items that are highly ranked.

4. The system of claim 1, wherein the computer-executable instructions, when executed, cause the processor to further analyze the subset of the plurality of data items to determine an item score for each data item of at least some of the plurality of data items.

5. The system of claim 4, wherein determining the item score for a first data item comprises evaluating a cost associated with the first item.

6. The system of claim 4, wherein determining the item score for a first data item comprises determining an availability of other data items similar to the first data item.

7. The system of claim 4, wherein determining the item score for a first data item comprises determining an expected demand of the first data item.

8. The system of claim 4, wherein determining the item score for a first data item comprises determining a prioritization of the first data item.

9. The system of claim 1, wherein determining the historical trend related to the entity comprises determining a target demographic for the entity.

10. The system of claim 1, wherein the data store is a hardware memory and the processor is a hardware processor.

11. A system comprising:

a data store configured to store computer-executable instructions; and

a processor, wherein the computer-executable instructions, when executed, configure the processor to;

obtain a plurality of events, wherein each event of the plurality of events comprises event information and one or more commercial units;

obtain user information comprising information provided by the user and a record of transactions for the user;

determine, for each commercial unit, a score, wherein the score is based at least in part on availability of the one or more commercial units and a comparison of the user information with the event information of the event;

determine a recommended subset of the plurality of events based at least in part on the user information and scores for each commercial unit;

generate for display a user interface comprising a list interface for display of;

the plurality of events, and

the recommended subset of events;

cause display of the user interface;

receive a selection of a first event from the plurality of events;

add the first event to the recommended subset of events to generate an updated subset of events;

analyze the updated subset of events to determine a package score; and

update the user interface to include;

an indication of the package score, and

a list of the updated subset of data events.

12. The system of claim 11, wherein the computer-executable instructions, when executed, further configure the processor to determine user preferences based on the obtained user information.

13. The system of claim 12, wherein determining the recommended subset of the plurality of events comprises determining a first ranking and a second ranking and combining the first and second rankings.

14. The system of claim 13, wherein determining the first ranking comprises comparing the determined user preferences with the obtained plurality of events.

15. The system of claim 14, wherein the computer-executable instructions, when executed, further configure the processor to determine a target demographic for the user based on the obtained user information.

16. The system of claim 15, wherein determining the second ranking comprises comparing the determined target demographic to the obtained plurality of events.