Fresh related search suggestions

• US 8,412,699 B1
• Filed: 06/12/2009
• Issued: 04/02/2013
• Est. Priority Date: 06/12/2009
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Mukherjee, Rajat, Das, Abhinandan S., Westall, Adam
• Primary Examiner(s): Jami, Hares
• Application Number:
  US12/483,992
• Time in Patent Office: 1,390 Days
• Field of Search: 707/705, 707/713, 707/721, 707/759, 707/765, 707/766, 707/767, 707/768, 707/999.3
• US Class Current: 707/713
• CPC Class Codes: G06F 16/2425 Iterative querying; Query formulation based on the results of a preceding query
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

Methods, systems, apparatus, including computer program products, for providing fresh related search suggestions in response to a user submitted query are presented. In one implementation, a plurality of prior queries are selected wherein each of the prior queries was submitted as a search query a number of times during a recent time period and satisfies a criterion. For each of the prior queries, the prior is selected as a candidate query based on one or more of: a determination that search results responsive to the prior query include a number of news results that satisfy a second threshold, and relevance data indicative of user behavior relative to the search results responsive to the prior query. In response to receiving a user query, one or more candidate queries are selected that match the user query.

Claims

1. A computer-implemented method comprising:

selecting a plurality of prior queries wherein each of the prior queries was submitted as a search query a number of times during a recent time period and satisfies a criterion, wherein the criterion is a rate of change in query frequency during the time period, a deviation from an expected query frequency during the time period, or a threshold number of occurrences of the query during the time period;

selecting one or more of the prior queries as candidate queries including determining, for each of the one or more prior queries, that a total number of search results responsive to the prior query include a threshold number of news results;

in response to receiving a user query, selecting from the candidate queries one or more queries that match the user query; and

providing one or more of the selected queries as related search suggestions for the user query.

2. The method of claim 1 further comprising ranking one or more of the matched queries based on the percentage of news results included in search results responsive to the matched query and relevance data indicative of user interaction with the search results responsive to the matched query.

3. The method of claim 1 wherein the recent time period is a most recent week, a most recent number of days, a most recent number of hours or a most recent number of minutes.

4. The method of claim 1 wherein the news results comprise one or more of:

news articles;

new blog results including information posted to micro blogs, mini blogs, and book-marking sites, new image results, new video results, and new web pages.

5. The method of claim 2 wherein relevance data is one or more of a click-through rate for the search results responsive to the matched query and a count of clicks on the search results responsive to the matched query.

6. The method of claim 1 wherein selecting from the candidate queries one or more queries that match the user query comprises selecting as a matched query, a candidate query that is one or more of a superstring of the user query, a refinement of the user query, or is near the user query.

7. The method of claim 6 wherein the matched query is a refinement of the user query if a number of users first submit the user query, and at a later time refine the user query to the matched query during the recent time period.

8. The method of claim 7 wherein a number of users is a count of users or a fraction of users relative to a number of users who submit the user query.

9. The method of claim 1, wherein determining a particular prior query, that a total number of search results responsive to the particular prior query include a threshold number of news results includes determining that one or more search results of N highest ranked search results of the total number of search results include are news results.

10. A system comprising:

a computer-readable storage device having instructions stored thereon; and

one or more data processing apparatus operable to execute the instructions and perform operations comprising;

selecting a plurality of prior queries wherein each of the prior queries was submitted as a search query a number of times during a recent time period and satisfies a criterion, wherein the criterion is a rate of change in query frequency during the time period, a deviation from an expected query frequency during the time period, or a threshold number of occurrences of the query during the time period;

selecting one or more of the prior queries as candidate queries including determining, for each of the one or more prior queries, that a total number of search results responsive to the prior query include a threshold number of news results;

in response to receiving a user query, selecting from the candidate queries one or more queries that match the user query; and

providing one or more of the selected queries as related search suggestions for the user query.

11. The system of claim 10 further comprising ranking one or more of the matched queries based on the percentage of news results included in search results responsive to the matched query and relevance data indicative of user interaction with the search results responsive to the matched query.

12. The system of claim 10 wherein the recent time period is a most recent week, a most recent number of days, a most recent number of hours or a most recent number of minutes.

13. The system of claim 10 wherein the news results comprise one or more of:

news articles;

new blog results including information posted to micro blogs, mini blogs, and book-marking sites, new image results, new video results, and new web pages.

14. The system of claim 11 wherein relevance data is one or more of a click-through rate for the search results responsive to the matched query and a count of clicks on the search results responsive to the matched query.

15. The system of claim 10 wherein selecting from the candidate queries one or more queries that match the user query comprises selecting as a matched query, a candidate query that is one or more of a superstring of the user query, a refinement of the user query, or is near the user query.

16. The system of claim 15 wherein the matched query is a refinement of the user query if a number of users first submit the user query, and at a later time refine the user query to the matched query during the recent time period.

17. The system of claim 16 wherein a number of users is a count of users or a fraction of users relative to a number of users who submit the user query.

18. A computer program product tangibly embodied in a non-transitory computer-readable storage device, the computer program product including instructions operable to cause one or more data processing apparatus to perform operations comprising:

selecting a plurality of prior queries wherein each of the prior queries was submitted as a search query a number of times during a recent time period and satisfies a criterion, wherein the criterion is a rate of change in query frequency during the time period, a deviation from an expected query frequency during the time period, or a threshold number of occurrences of the query during the time period;

selecting one or more of the prior queries as candidate queries including determining, for each of the one or more prior queries, that a total number of search results responsive to the prior query include a threshold number of news results;

in response to receiving a user query, selecting from the candidate queries one or more queries that match the user query; and

providing one or more of the selected queries as related search suggestions for the user query.

19. The program product of claim 18 further comprising ranking one or more of the matched queries based on the percentage of news results included in search results responsive to the matched query and relevance data indicative of user interaction with the search results responsive to the matched query.

20. The program product of claim 18 wherein the recent time period is a most recent week, a most recent number of days, a most recent number of hours or a most recent number of minutes.

21. The program product of claim 18 wherein the news results comprise one or more of:

news articles;

new blog results including information posted to micro blogs, mini blogs, and book-marking sites, new image results, new video results, and new web pages.

22. The program product of claim 19 wherein relevance data is one or more of a click-through rate for the search results responsive to the matched query and a count of clicks on the search results responsive to the matched query.

23. The program product of claim 18 wherein selecting from the candidate queries one or more queries that match the user query comprises selecting as a matched query, a candidate query that is one or more of a superstring of the user query, a refinement of the user query, or is near the user query.

24. The program product of claim 23 wherein the matched query is a refinement of the user query if a number of users first submit the user query, and at a later time refine the user query to the matched query during the recent time period.

25. The program product of claim 24 wherein a number of users is a count of users or a fraction of users relative to a number of users who submit the user query.