Methods and systems for selecting and presenting content on a first system based on user preferences learned on a second system

• US 10,599,704 B2
• Filed: 01/15/2019
• Issued: 03/24/2020
• Est. Priority Date: 03/06/2006
• Status: Active Grant

• Current Assignee: Veveo, Inc. (Adeia Inc.)
• Original Assignee: Veveo, Inc. (Adeia Inc.)
• Inventors: Aravamudan, Murali, Rajasekharan, Ajit, Ramakrishnan, Kajamalai G.
• Primary Examiner(s): Hill, Stanley K.
• Application Number:
  US16/248,308
• Publication Number:
  US 20190146990A1
• Time in Patent Office: 434 Days
• CPC Class Codes: G06F 16/152 using file content signatures, e.g. hash values
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2462 Approximate or statistical queries
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/437 Administration of user profiles, e.g. generation, initialisation, adaptation, distribution
• CPC Class Codes: G06F 16/438 Presentation of query results
• CPC Class Codes: G06F 16/686 using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/44224 : Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4524 : involving the geographical location of the client retrieval from the Internet by querying based on geographical locations G06F16/9537; systems specially adapted for using geographical information in broadcast systems H04H60/70; protocols in which the network application is adapted for the location of the user terminal in communication control or processing H04L67/52; services making use of the location of users or terminals in wireless networks H04W4/02; locating users or terminals in wireless networks H04W64/00
• CPC Class Codes: H04N 21/4532 : involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/466 : Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4828 : for searching program descriptors retrieval of video data G06F16/739
• CPC Class Codes: Y10S 707/99933 : Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 : Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99937 : Sorting
• CPC Class Codes: Y10S 707/99943 : Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99945 : Object-oriented database structure processing

Abstract

A method of selecting and presenting content on a first system based on user preferences learned on a second system is provided. The method includes receiving a user'"'"'s input for identifying items of the second content system and, in response thereto, presenting a subset of items of the second content system and receiving the user'"'"'s selection actions thereof. The method includes analyzing the selected items to learn the user'"'"'s content preferences for the content of the second content system and determining a relationship between the content of the first and second content systems to determine preferences relevant to items of the first content system. The method includes, in response subsequent user input for items of the first content system, selecting and ordering a collection of items of the first content system based on the user'"'"'s learned content preferences determined to be relevant to the items of the first content system.

Claims

1. A computing device comprising:

a processor;

a display operably coupled to the processor; and

a memory coupled to the processor and storing computer-readable instructions, the computer-readable instructions configured to cause a display of a first set of content items received from a first dataspace, the first set of content items being selected and presented based, at least in part, on user interactions with a second dataspace having a second set of content items, each respective content item of the second set of content items having at least one descriptive term to describe the respective content item, wherein the first dataspace is configured to;

(i) receive the at least one descriptive term associated with the second set of content items;

(ii) analyze one or more descriptive terms to learn content preferences for a user;

(iii) determine a subset of learned content preferences that is relevant to the first set of content items; and

(iv) cause the computing device to output on the display, the first set of content items that is received by the computing device from the first dataspace at a time subsequent to the user interactions with the second dataspace, the first set of content items being displayed in accordance with the subset of learned content preferences.

2. The computing device of claim 1, wherein displaying the first set of content items in accordance with the subset of learned content preferences includes at least one item of the first set of content items being selected and ordered based on the subset of learned content preferences.

3. The computing device of claim 1, wherein:

the first dataspace is provided by a content provider; and

the second dataspace is provided by an online retailer that is not affiliated with the content provider.

4. The computing device of claim 1, wherein:

the second set of content items is associated with one or more products offered for sale within the second dataspace; and

the at least one descriptive term comprises action information related to an action taken with respect to the one or more products offered for sale.

5. The computing device of claim 4, wherein:

the action information includes a nature of the action that indicates whether a purchase was made; and

the action information includes a detail of the action that indicates a type of good that was purchased.

6. The computing device of claim 1, wherein the first dataspace is configured to compute a probability that the user is likely to perform an action in the second dataspace based, at least in part, on content within the first set of content items.

7. The computing device of claim 1, wherein the at least one descriptive term is stored locally on the computing device before being transmitted to the first dataspace.

8. The computing device of claim 7, wherein the at least one descriptive term is stored as a web-browsing cookie on the computing device.

9. A networked learning system comprising:

a computing device having a display and configured to;

display a first set of content items received from a first content system at a first time; and

display a second set of content items received from a second content system at a second time that is prior to the first time, each content item having at least one descriptive term that describes the content item; and

a personal preference information service that is configured to;

receive descriptive terms associated with the second set of content items and analyze the descriptive terms to determine a subset of learned content preferences that is relevant to the first set of content items, wherein;

the computing device is configured to display the first set of content items in accordance with the subset of learned content preferences obtained from the second set of content items while the computing device is in communication with the first content system.

10. The networked learning system of claim 9, wherein the first set of content items includes at least one item that is selected and ordered based on the subset of learned content preferences.

11. The networked learning system of claim 9, wherein:

the computing device is further configured to display a third set of content items while the computing device is in communication with a third content system;

the personal preference information service receives additional descriptive terms that are associated with the third set of content items; and

the subset of learned content preferences is based, in part, on the additional descriptive terms.

12. The networked learning system of claim 9, wherein:

the first content system is provided by an online content provider; and

the second content system is provided by a third-party online retailer.

13. The networked learning system of claim 12, wherein the personal preference information service is configured to compute a probability that a user of the computing device is likely to purchase a product offered by the third-party online retailer based, at least in part, on content provided by the online content provider.

14. The computing device of claim 12, wherein at least one item is selected and ordered based, at least in part, on the computed probability.

15. A content provider operably coupled to a user device over a computer network, the content provider configured to:

cause a display of a first set of first content items on the user device, the first set of first content items being selected and presented based, at least in part, on user interactions with an online retailer, the online retailer being distinct from the content provider and providing a second set of second content items, each respective second content item having at least one descriptive term to describe the respective second content item;

receive the at least one descriptive term associated with the second set of second content items;

analyze one or more descriptive terms to learn content preferences for a user;

determine a subset of learned content preferences that is relevant to the first set of first content items; and

cause the display of the first set of first content items on a display of the user device in accordance with the subset of learned content preferences, the content provider configured to cause the display of the first set of first content items at a time subsequent to the user interactions with the online retailer.

16. The content provider of claim 15, wherein:

the content provider is configured to compute a probability that the user is likely to make a purchase with the online retailer based, at least in part, on content provided by the content provider; and

the first set of first content items includes at least one item selected and ordered based on the subset of learned content preferences and the computed probability.

17. The content provider of claim 15, wherein:

the online retailer offers products including books, movies, or music; and

the subset of learned content preferences includes information regarding a genre related to the products offered by the online retailer.

18. The content provider of claim 15, wherein:

the content provider is configured to receive information related to a subsequent user interaction with the online retailer subsequent to the display of the first set of first content items on the user device; and

the content provider is configured to update the content preferences for the user based on the subsequent user interaction.

19. The content provider of claim 15, wherein:

the online retailer is a first online retailer;

the content provider is configured to receive additional descriptive terms associated with a third set of third content items provided by a second online retailer that is distinct from the first online retailer; and

the content preferences are based, as least in part, on the additional descriptive terms.

20. The content provider of claim 19, wherein the user device is configured to display the first set of first content items on a display of the user device subsequent to user interactions with the first online retailer and the second online retailer.