Endorsing search results

• US 9,177,063 B2
• Filed: 06/13/2014
• Issued: 11/03/2015
• Est. Priority Date: 06/30/2004
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Dynin, Misha
• Primary Examiner(s): Reyes, Mariela
• Assistant Examiner(s): VU, THONG H
• Application Number:
  US14/304,571
• Publication Number:
  US 20140297615A1
• Time in Patent Office: 508 Days
• Field of Search: 707/1/1, 707/600, 707/101, 707/200, 707/724, 707/733, 707/706, 705/4, 705/1, 705/10
• US Class Current: 1/1
• 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

Abstract

Methods and systems for improving user search experience with a search engine by providing a way for associated users to create and share personalized lists of article identifiers through endorsements of articles. Search endorsements can be used to personalize the search engine'"'"'s ranking of articles by offering a way for users to re-rank the article identifiers for themselves and for those who trust them.

Claims

1. A computer-implemented method comprising:

receiving, by a computer system comprising one or more servers from particular members of a member network, machine-readable endorsement information that characterizes the particular members'"'"' ratings of various articles;

receiving member profile information specifying that one or more members of the member network are experts in one or more respective fields;

receiving, by the computer system, a first search query from a first user in the member network;

determining, by the computer system, that the first search query relates to a particular field;

identifying, from an article index by the computer system, a first plurality of articles that are responsive to the first search query;

identifying, by the computer system from profile information of the members of the member network, one or more experts in the member network that are each an expert in the particular field to which the computer system determined the first search query relates;

identifying, from a repository of member network data for the member network, a second plurality of articles that are responsive to the first search query and that have been endorsed by particular members in the member network, wherein the repository of member network data is different from the article index;

determining that a first article in the second plurality of articles has been endorsed by an expert in the one or more experts in the member network who are each an expert in the particular field to which the computer system determined the first search query relates;

generating, by the computer system, a plurality of article identifiers for articles that include articles from the first and second pluralities of articles;

ranking, by the computer system, using the endorsements for articles in the second plurality of articles, the first article that has been endorsed by the expert in the particular field to which the first search query relates with a higher ranking than a second article that was not endorsed by an expert in the particular field to which the first search query relates; and

responding, by the computer system, to the first search query with the plurality of article identifiers according to the ranking including a first article identifier for the first article and a second article identifier for the second article.

2. The method of claim 1, comprising:

receiving profiles of the members in the member network, wherein each of the profiles includes machine-readable endorsement information submitted by the respective member that characterizes the respective member'"'"'s ratings of various articles, wherein at least one of the profiles identifies the corresponding member in the member network that provided the respective endorsement information as an expert in the particular field.

3. The method of claim 1, comprising receiving machine-readable endorsement information that characterizes members'"'"' ratings of various articles, wherein the members are members in the member network by:

receiving a collection of search queries submitted by one or more members in the member network;

receiving a collection of article identifiers identifying articles that are responsive to the search queries;

receiving a collection of numeric ratings of at least one of the articles identified by the article identifiers; and

updating, for each of the one or more members in the member network, corresponding profile information using numeric ratings from the collection of numeric ratings and the article identifiers for the articles rated by the corresponding member.

4. The method of claim 3, wherein receiving the collection of search queries submitted by the one or more members in the member network comprises receiving at least one search query that is identical to the first search query.

5. The method of claim 3, wherein receiving the collection of search queries submitted by the one or more members in the member network comprises receiving search queries that are relevant to the first search query.

6. The method of claim 3, wherein receiving a collection of the numeric ratings of the at least one of the articles each comprises receiving one or more of:

a binary positive or negative rating,

a scaled grade, or

a comment characterizing a member'"'"'s rating of an article.

7. The method of claim 1, comprising:

receiving machine-readable endorsement information that characterizes members'"'"' ratings of various articles, wherein the members are members in the member network and some of the endorsement information identifies the corresponding member in the member network that provided the respective endorsement information as an expert in the particular field; and

providing a first member from the member network with a financial incentive in response to an endorsement of a particular article in the second plurality of articles.

8. The method of claim 1, comprising:

receiving machine-readable endorsement information that characterizes members'"'"' ratings of various articles, wherein the members are members in the member network and some of the endorsement information identifies the corresponding member in the member network that provided the respective endorsement information as an expert in the particular field; and

determining that a first member of the member network other than the first user has endorsed a particular article in the second plurality of articles, wherein the endorsement information comprises an article identifier that identifies the particular article and the first member'"'"'s rating of the particular article.

9. The method of claim 1, comprising receiving machine-readable endorsement information that characterizes members'"'"' ratings of various articles independent of any search query, wherein the members are members in the member network and some of the endorsement information identifies the corresponding member in the member network that provided the respective endorsement information as an expert in the particular field.

10. The method of claim 1, comprising receiving machine-readable endorsement information that characterizes members'"'"' ratings of various articles based on a scaled grade, wherein the members are members in the member network and some of the endorsement information identifies the corresponding member in the member network that provided the respective endorsement information as an expert in the particular field.

11. The method of claim 1, comprising:

determining that a first member of the member network other than the first user has endorsed a particular article in the second plurality of articles, wherein the plurality of article identifiers includes an identifier for the particular article;

determining, from among a plurality of different types or degrees of associations between the members in the member network, a particular type or degree of an association in the member network between the first user and the first member; and

ranking articles that correspond with the plurality of article identifiers using the particular type or degree of the association in the member network between the first member and the first user, wherein responding to the first search query with the plurality of article identifiers comprises formatting a response in an arrangement that corresponds to the ranking of the articles using the particular type or degree of the association in the member network between the first member and the first user.

12. The method of claim 11, wherein determining that the first member of the member network other than the first user has endorsed the particular article in the second plurality of articles comprises determining that the first member'"'"'s endorsement of the particular article comprises a comment characterizing the first member'"'"'s rating of the particular article.

13. The method of claim 11, wherein determining the particular type or degree of the association in the member network between the first user and the first member comprises determining a degree of the association in the member network between the first member and the first user that indicates a number of intermediate relationships that separate the first member and the first user.

14. The method of claim 11, wherein determining the particular type or degree of the association in the member network between the first user and the first member comprises determining an association between the first user and the first member that comprises one of a friendship association, a business association, a family association, a community association, or a school association.

15. The method of claim 11, comprising:

determining a level of the particular type of association in the member network between the first user and the first member, the level indicating a relative strength of the particular type of association between the first user and the first member; and

ranking the articles in the plurality of articles using the level of the particular type of association in the member network between the first user and the first member.

16. The method of claim 11, wherein determining that the first member has endorsed the particular article in the second plurality of articles includes selecting the first member from among a plurality of members in the member network based on the first member being associated with the first user in the member network or based on the first member being associated with the first search query.

17. The method of claim 11, wherein ranking the articles in the plurality of articles comprises re-ranking an order of the articles in the first plurality of articles that are included in the plurality of articles using the first member'"'"'s endorsement of the particular article.

18. The method of claim 17 wherein re-ranking the order of the articles in the first plurality of articles that are included in the plurality of articles comprises ranking the particular article above another article for which endorsement information has not been received when, in the absence of the first member'"'"'s endorsement of the particular article, the other article would be more relevant to the first search query than the particular article such that the other article would be ranked above the particular article.

19. The method of claim 1, wherein identifying the one or more experts in the member network that are each an expert in the particular field to which the computer system determined the first search query relates comprises determining that at least one of the one or more experts in the member network is an expert in the particular field using corresponding professional information or corresponding educational information in the profile information for the corresponding expert.

20. The method of claim 1, comprising receiving a machine-readable endorsement of the first article by the expert in the member network who is an expert in the particular field.

21. A system comprising:

one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising;

receiving, from particular members of a member network, machine-readable endorsement information that characterizes the particular members'"'"' ratings of various articles;

receiving member profile information specifying that one or more members of the member network are experts in one or more respective fields;

receiving a first search query from a first user in the member network;

determining that the first search query relates to a particular field;

identifying, from an article index, a first plurality of articles that are responsive to the first search query;

identifying, from profile information of the members of the member network, one or more experts in the member network that are each an expert in the particular field to which the first search query relates;

identifying, from a repository of member network data for the member network, a second plurality of articles that are responsive to the first search query and that have been endorsed by particular members in the member network, wherein the repository of member network data is different from the article index;

determining that a first article in the second plurality of articles has been endorsed by an expert in the one or more experts in the member network who are each an expert in the particular field to which the first search query relates;

generating a plurality of article identifiers for articles that include articles from the first and second pluralities of articles;

ranking, using the endorsements for articles in the second plurality of articles, the first article that has been endorsed by the expert in the particular field to which the first search query relates with a higher ranking than a second article that was not endorsed by an expert in the particular field to which the first search query relates; and

responding to the first search query with the plurality of article identifiers according to the ranking including a first article identifier for the first article and a second article identifier for the second article.

22. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:

receiving, from particular members of a member network, machine-readable endorsement information that characterizes the particular members'"'"' ratings of various articles;

receiving member profile information specifying that one or more members of the member network are experts in one or more respective fields;

receiving a first search query from a first user in the member network;

determining that the first search query relates to a particular field;

identifying, from an article index, a first plurality of articles that are responsive to the first search query;

identifying, from profile information of the members of the member network, one or more experts in the member network that are each an expert in the particular field to which the first search query relates;

identifying, from a repository of member network data for the member network, a second plurality of articles that are responsive to the first search query and that have been endorsed by particular members in the member network, wherein the repository of member network data is different from the article index;

determining that a first article in the second plurality of articles has been endorsed by an expert in the one or more experts in the member network who are each an expert in the particular field to which the first search query relates;

generating a plurality of article identifiers for articles that include articles from the first and second pluralities of articles;

ranking, using the endorsements for articles in the second plurality of articles, the first article that has been endorsed by the expert in the particular field to which the first search query relates with a higher ranking than a second article that was not endorsed by an expert in the particular field to which the first search query relates; and

responding to the first search query with the plurality of article identifiers according to the ranking including a first article identifier for the first article and a second article identifier for the second article.