Systems and methods for determining an article association measure

• US 8,131,754 B1
• Filed: 06/30/2004
• Issued: 03/06/2012
• Est. Priority Date: 06/30/2004
• Status: Expired due to Fees

• Current Assignee: Google Inc. (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Lawrence, Stephen R., Wang, Niniane
• Primary Examiner(s): Saeed, Usmaan
• Assistant Examiner(s): Ahluwalia, Navneet K
• Application Number:
  US10/882,066
• Time in Patent Office: 2,806 Days
• Field of Search: 707 1- 10, 707100-1041, 707200-205, 707/771, 707/758
• US Class Current: 707/771
• CPC Class Codes: G06F 16/903 Querying for retrieval from the web G06F16/953
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

Systems and methods for determining an article association measure are described. In one described method, a computer program receives a first article identifier associated with a first attribute and a second article identifier associated with a second attribute and determines a similarity measure of the first article identifier to the second article identifier based at least in part on the first attribute and on the second attribute. The similarity measure may provide a means for associating various article identifiers so that they may be, for example, retrieved and/or ranked in subsequent search queries.

Claims

1. A method comprising:

capturing a plurality of events, wherein the events comprise user interactions with articles on a client device, and wherein the captured events are generated by user interactions involving multiple ones of the plurality of client applications;

receiving a first article identifier identifying a first article and associated with a first date-time attribute, the first date-time attribute associated with a first one of the plurality of events;

receiving a second article identifier identifying a second article and associated with a second date-time attribute, the second date-time attribute associated with a second one of the plurality of events; and

determining an association measure of the first article identifier to the second article identifier based at least in part on the first date-time attribute and on the second date-time attribute, the determining comprising;

determining a difference between the first date-time attribute and the second date-time attribute,

comparing the difference to a threshold,

setting the association measure equal to a first value if the difference exceeds the threshold, and

setting the association measure equal to a second value if the difference does not exceed the threshold.

2. The method of claim 1, wherein the difference is inversely proportional to the association measure.

3. The method of claim 1, wherein the association measure comprises a plurality of association measures, and further comprising combining the plurality of association measures to create a combined association measure.

4. The method of claim 1, further comprising normalizing the association measure to create a normalized association measure.

5. The method of claim 1, wherein the association measure is one of a linear, piecewise, or exponential function, wherein the measure indicates higher association for smaller differences.

6. The method of claim 1, wherein the first article identifier is further associated with a first content attribute and the second article identifier is further associated with a second content attribute, the method further comprising determining the association measure of the first article identifier to the second article identifier based at least in part on the first content attribute and on the second content attribute.

7. The method of claim 1, wherein the first article identifier is further associated with a first metadata attribute and the second article identifier is further associated with a second metadata attribute, the method further comprising determining the association measure of the first article identifier to the second article identifier based at least in part on the first metadata attribute and on the second metadata attribute.

8. The method of claim 1, wherein the association score is determined by an indexer as part of indexing and applied as part of execution of a query.

9. The method of claim 1, wherein the association score is determined as part of execution of a query.

10. The method of claim 1, further comprising:

receiving a query;

receiving search results as a result of query execution, the search results comprising the first article identifier and omitting the second article identifier;

identifying the second article identifier as being related to the first article identifier based at least in part on the association measure; and

displaying the second article identifier along with the received search results.

11. The method of claim 7, wherein the first metadata attribute comprises an author.

12. The method of claim 7, wherein the first metadata attribute comprises an organization.

13. The method of claim 3, wherein combining the plurality of association measures to create the combined association measure comprises weighting each association measure according to a weight corresponding to a type of the association measure.

14. A non-transitory computer-readable storage medium on which is encoded program code, the program code comprising:

program code for capturing a plurality of events, wherein the events comprise user interactions with articles on a client device, and wherein the events are generated by user interactions involving multiple ones of the plurality of client applications;

program code for receiving a first article identifier identifying a first article and associated with a first date-time attribute, the first date-time attribute associated with a first one of the plurality of events;

program code for receiving a second article identifier identifying a second article and associated with a second date-time attribute, the second date-time attribute associated with a second one of the plurality of events; and

program code for determining an association measure of the first article identifier to the second article identifier based at least in part on the first date-time attribute and on the second date-time attribute, the determining comprising;

determining a difference between the first date-time attribute and the second date-time attribute,

comparing the difference to a threshold,

setting the association measure equal to a first value if the difference exceeds the threshold, and

setting the association measure equal to a second value if the difference does not exceed the threshold.

15. The computer-readable storage medium of claim 14, wherein the association measure comprises a plurality of association measures, and further comprising program code for combining the plurality of association measures to create a combined association measure.

16. The computer-readable storage medium of claim 14, further comprising program code for normalizing the association measure to create a normalized association measure.

17. A computer system, comprising:

a computer processor; and

a non-transitory computer-readable medium storing processor-executable program instructions that when executed by the processor perform actions comprising;

capturing a plurality of events, wherein the events comprise user interactions with articles on a client device, and wherein the captured events are generated by user interactions involving multiple ones of the plurality of client applications;

receiving a first article identifier identifying a first article and associated with a first date-time attribute, the first date-time attribute associated with a first one of the plurality of events;

receiving a second article identifier identifying a second article and associated with a second date-time attribute, the second date-time attribute associated with a second one of the plurality of events; and

determining an association measure of the first article identifier to the second article identifier based at least in part on the first date-time attribute and on the second date-time attribute, the determining comprising;

determining a difference between the first date-time attribute and the second date-time attribute, comparing the difference to a threshold, setting the association measure equal to a first value if the difference exceeds the threshold, and setting the association measure equal to a second value if the difference does not exceed the threshold.

18. The computer system of claim 17, wherein the first article identifier is further associated with a first content attribute and the second article identifier is further associated with a second content attribute, the actions further comprising determining the association measure of the first article identifier to the second article identifier based at least in part on the first content attribute and on the second content attribute.

19. The computer system of claim 17, wherein the first article identifier is further associated with a first metadata attribute and the second article identifier is further associated with a second metadata attribute, the actions further comprising determining the association measure of the first article identifier to the second article identifier based at least in part on the first metadata attribute and on the second metadata attribute.

20. The computer system of claim 19, wherein the first metadata attribute comprises an author.