System and method for returning prioritized content

• US 10,191,988 B2
• Filed: 10/28/2015
• Issued: 01/29/2019
• Est. Priority Date: 10/28/2015
• Status: Active Grant

• Current Assignee: Sony Corporation (Sony Group Corp.)
• Original Assignee: Sony Mobile Communications Incorporated (Sony Group Corp.)
• Inventors: Gustavsson, Jonas, Isberg, Anders
• Primary Examiner(s): Mackes, Kris E
• Assistant Examiner(s): Bui, Tiffany Thuy
• Application Number:
  US14/924,961
• Publication Number:
  US 20170124196A1
• Time in Patent Office: 1,189 Days
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A prioritized list of items available via an electronic user device is provided to a user. The user has relations categorized in a social graph for which activity is crawled to detect interactive behavior with objects made by the relations via respective electronic devices. The prioritizing includes identifying items for the list; determining a relative level of the user'"'"'s contextual affinity with one or more of the list items, contextual affinity to a list item characterized by connectedness of a context of the user'"'"'s current use of the electronic user device to a manner in which a relation has had interactive behavior with one of the objects that corresponds to the list item; and ranking the list items according to the relative levels of affinity.

Claims

1. A method of providing a prioritized list of items available via an electronic user device to a user, comprising:

identifying, by one or more processors having access to a memory, a plurality of relations of the user;

classifying, by the one or more processors, each of the plurality of relations of the user into at least one of a plurality of classifications in a social graph;

for each of the plurality of relations of the user, identifying, by the one or more processors, a set of objects associated with a relation of the user, wherein the set of objects is identified based on interactions that the relation has with an electronic device; and

indexing, by the one or more processors, each of the identified objects in a multidimensional object matrix stored in the memory;

generating, by the one or more processors and for an object in the set of objects, multidimensional ranking data, wherein each dimension of the multidimensional ranking data is based on a different manner in which a relation has had interactive behavior with the object;

indexing, by the one or more processors, each dimension of the multidimensional ranking data in the multidimensional object matrix, wherein the indexing associates each dimension of the multidimensional ranking data with the object;

identifying, by the one or more processors, items for the list, wherein the list items are search results for a user-defined search query, the search results having relative priority based on at least a number of inbound links to each search result;

determining, by the one or more processors, a relative level of the user'"'"'s contextual affinity with one or more of the list items, contextual affinity to a list item characterized by connectedness of a context of the user'"'"'s current use of the electronic user device to a dimension of the multidimensional ranking data associated with the object when the object corresponds to the list item; and

ranking, by the one or more processors, the list items according to the relative levels of affinity, wherein ranking the list items according to the relative levels of affinity includes assiqninq a first weiqhtinq factor to the relative level of affinity and a second weighting factor to the relative priority based on the number of inbound links, and wherein the ranking is based on a combination of the weighted level of affinity and the weighted priority based on the number of inbound links.

2. The method of claim 1, wherein the list items include media content items or media content suggestions.

3. The method of claim 1, wherein context of the user'"'"'s current use of the electronic user device is defined by one or more of a type of the electronic user device, a location of the user, and an activity in which the user is engaged in addition to using the electronic user device.

4. The method of claim 1, wherein the interactive behavior with the object is one or more of accessing or consuming the object, a number of times a link is set to the object, frequency of use of the object, and bookmarking of the object.

5. The method of claim 1, wherein the relations are classified in two or more relation type categories representing different context roles in which the user engages at different times.

6. A computing system configured to provide a prioritized list of items available via an electronic user device to a user, the computing system comprising:

a memory that stores a software-based ranking function comprised of executable instructions and a multidimensional object matrix; and

a processor that executes the executable instructions and by execution of the executable instructions, the computer system;

identifies a plurality of relations of the user;

classifies each of the plurality of relations of the user into at least one of a plurality of classifications in a social graph;

identifies, for each of the plurality of relations of the user, a set of objects associated with a relation of the user, wherein the set of objects is identified based on interactions that the relation has with an electronic device; and

indexes each of the identified objects in a multidimensional object matrix stored in the memory;

generates, for an object in the set of objects, multidimensional ranking data, wherein each dimension of the multidimensional ranking data is based on a different manner in which a relation has had interactive behavior with the object;

indexes each dimension of the multidimensional ranking data in the multidimensional object matrix, wherein the indexing associates each dimension of the multidimensional ranking data with the object;

identifies items for the list, wherein the list items are search results for a user-defined search query, the search results having relative priority based on at least a number of inbound links to each search result;

determines a relative level of the user'"'"'s contextual affinity with one or more of the list items, contextual affinity to a list item characterized by connectedness of a context of the user'"'"'s current use of the electronic user device to a dimension of the multidimensional ranking data associated with the object when the object corresponds to the list item; and

ranks the list items according to the relative levels of affinity, wherein ranking the list items according to the relative levels of affinity includes assigning a first weighting factor to the relative level of affinity and a second weighting factor to the relative priority based on the number of inbound links, and wherein the ranking is based on a combination of the weighted level of affinity and the weighted priority based on the number of inbound links.

7. The computing system of claim 6, wherein the list items include media content items or media content suggestions.

8. The computing system of claim 6, wherein context of the user'"'"'s current use of the electronic user device is defined by one or more of a type of the electronic user device, a location of the user, and an activity in which the user is engaged in addition to using the electronic user device.

9. The computing system of claim 6, wherein the interactive behavior with the object is one or more of accessing or consuming the object, a number of times a link is set to the object, frequency of use of the object, and bookmarking of the object.

10. The computing system of claim 6, wherein the relations are classified in two or more relation type categories representing different context roles in which the user engages at different times.

11. A non-transitory computer readable storage medium storing executable instructions for providing a prioritized list of items available via an electronic user device to a user, which executable instructions, when executed by a computing system, cause the computing system to:

identify a plurality of relations of the user;

classify each of the plurality of relations of the user into at least one of a plurality of classifications in a social graph;

identify, for each of the plurality of relations of the user, a set of objects associated with a relation of the user, wherein the set of objects is identified based on interactions that the relation has with an electronic device;

index each of the identified objects in a multidimensional object matrix stored in a memory accessible to the computing system;

generate, for an object in the set of objects, multidimensional ranking data, wherein each dimension of the multidimensional ranking data is based on a different manner in which a relation has had interactive behavior with the object;

index each dimension of the multidimensional ranking data in the multidimensional object matrix, wherein the indexing associates each dimension of the multidimensional ranking data with the object;

identify items for the list, wherein the list items are search results for a user-defined search query, the search results having relative priority based on at least a number of inbound links to each search result;

determine a relative level of the user'"'"'s contextual affinity with one or more of the list items, contextual affinity to a list item characterized by connectedness of a context of the user'"'"'s current use of the electronic user device to a dimension of the multidimensional ranking data associated with the object when the object corresponds to the list item; and

rank the list items according to the relative levels of affinity, wherein ranking the list items according to the relative levels of affinity includes assigning a first weighting factor to the relative level of affinity and a second weighting factor to the relative priority based on the number of inbound links, and wherein the ranking is based on a combination of the weighted level of affinity and the weighted priority based on the number of inbound links.

12. The non-transitory computer readable medium of claim 11, wherein the list items include media content items or media content suggestions.

13. The non-transitory computer readable medium of claim 11, wherein context of the user'"'"'s current use of the electronic user device is defined by one or more of a type of the electronic user device, a location of the user, and an activity in which the user is engaged in addition to using the electronic user device.

14. The non-transitory computer readable medium of claim 11, wherein the interactive behavior with the object is one or more of accessing or consuming the object, a number of times a link is set to the object, frequency of use of the object, and bookmarking of the object.

15. The non-transitory computer readable medium of claim 11, wherein the relations are classified in two or more relation type categories representing different context roles in which the user engages at different times.