Biasing queries to determine suggested queries

• US 7,844,599 B2
• Filed: 05/08/2006
• Issued: 11/30/2010
• Est. Priority Date: 08/24/2005
• Status: Active Grant

• Current Assignee: Jollify Management Limited
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Maghoul, Farzin, Kasperski, Richard
• Primary Examiner(s): Trujillo; James
• Assistant Examiner(s): Moser; Bruce M
• Application Number:
  US11/430,488
• Publication Number:
  US 20070050339A1
• Time in Patent Office: 1,667 Days
• Field of Search: 707/3, 707/4, 707/7, 707/999.003, 707/999.004, 707/999.007, 707/713, 707/723, 707/767, 707/759, 715/816
• US Class Current: 707/713
• CPC Class Codes: G06F 16/9032 Query formulation

Abstract

Applying a bias when determining a suggested search query. Examples of biases that can be applied include, but are not limited to, temporal biases and monetization biases. Temporal biasing involves increasing a weight associated with a search query, based on a temporal attribute associated with the query. Search queries may also have associated with them a parameter such as frequency, count, etc. One of these parameters may serve as a weight. In order to determine suggested search queries, the temporal attribute is used to modify or bias the parameter (e.g., frequency parameter). Thus, the weight of the search query is modified to temporally bias the query. The suggested search queries are determined based on the biased parameter.

Claims

1. A method comprising receiving a not-yet-submitted user search query from a client node;

wherein the not-yet-submitted user search query is a partial, not completely formed search query;

wherein the not-yet-submitted user search query is received after the steps of;

prior to the user finalizing and submitting the search query, determining that the not-yet-submitted user search query meets search initiation criteria;

in response to receiving the not-yet submitted user search query, generating a set of suggested query candidates;

generating a biased parameter, wherein the parameter is associated with a suggested query candidate of the set of suggested query candidates, and the parameter is biased based on an attribute associated with the suggested query candidate;

selecting one or more of suggested query candidates of the set of suggested query candidates to be suggested queries for the search query based on the biased parameter associated with the suggested query candidate;

determining relevance of at least one of the suggested queries of the one or more suggested query candidates;

in response to determining that the relevance of said at least one of the suggested queries meets or exceeds a relevance threshold, providing said at least one of the suggested queries to the client node;

receiving, from the client node, a search request including one of the suggested queries as a completely formed query; and

in response to receiving the search request including one of the suggested queries as a completely formed query, sending search results back to the client node;

wherein search results include a list of links to files or pages.

2. The method of claim 1, wherein the parameter that is associated with said suggested query candidate is based on a count of how many times the suggested query candidate was previously selected.

3. The method of claim 1, wherein the attribute is a monetization value that reflects a monetary value that is associated with the suggested query candidate.

4. The method of claim 1, further comprising determining the suggested query candidates based, at least in part, on a count of how many times the suggested query candidates have been received from users.

5. The method of claim 1, wherein the suggested queries comprise at least one of:

a) a predictive search query wherein a predictive search query is determined by predicting what the search query will be when completed;

or

b) an alternative search query wherein an alternative search query differs from the predicted search query and is determined based on the predicted search query.

6. A method as recited in claim 1, wherein the attribute is information associated with a user that submitted the user search query.

7. The method of claim 1, wherein the suggested queries comprise at least one of:

a) a predictive search query wherein a predictive search query is determined by predicting what the search query will be when completed;

or

b) an alternative search query wherein an alternative search query differs from the predicted search query and is determined based on the predicted search query.

8. The method of as recited in claim 1, wherein a set of pre-defined search queries are formed prior to receiving the not-yet-submitted user search query.

9. The method of claim 8, wherein generating a biased parameter is performed prior to receiving a not-yet-submitted user search query;

and

wherein the biased parameter is associated with a pre-defined search query of the set of pre-defined search queries.

10. The method of claim 1, wherein at least one suggested query candidate is selected by performing:

determining the current date;

determining an event taking place within a certain time window from the current date;

in response to determining, generating a suggested query term containing said event.

11. The method of claim 1, generating a set of suggested query candidates is based on previous queries issued by at least one user other than said user;

wherein said previous queries are associated with a country of origin; and

selecting one or more suggested query candidates of the set of suggested query candidates gives a bias to query candidates that have the same country of origin as said user.

12. The method of claim 1, wherein the search initiation criteria is only met when the user has completed entering a word.

13. The method of claim 1, wherein the search initiation criteria is based on how long it has been since the user last entered a character in the not-yet submitted user search query.

14. A machine-readable volatile or non-volatile medium storing instructions, wherein said instructions are instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of:

receiving a not-yet-submitted user search query from a client node;

wherein the not-yet-submitted user search query is a partial, not completely formed search query;

wherein the not-yet-submitted user search query is received after the steps of;

prior to the user finalizing and submitting the search query, determining that the not-yet-submitted user search query meets search initiation criteria;

in response to receiving the not-yet submitted user search query, generating a set of suggested query candidates;

generating a biased parameter, wherein the parameter is associated with a suggested query candidate of the set of suggested query candidates, and the parameter is biased based on an attribute associated with the suggested query candidate;

selecting one or more of suggested query candidates of the set of suggested query candidates to be suggested queries for the search query based on the biased parameter associated with the suggested query candidate;

determining relevance of at least one of the suggested queries of the one or more suggested query candidates;

in response to determining that the relevance of said at least one of the suggested queries meets or exceeds a relevance threshold, providing said at least one of the suggested queries to the client node;

receiving, from the client node, a search request including one of the suggested queries as a completely formed query; and

in response to receiving the search request including one of the suggested queries as a completely formed query, sending search results back to the client node;

wherein search results include a list of links to files or pages.

15. The machine-readable volatile or non-volatile medium of claim 14, wherein the parameter that is associated with said suggested query candidate is based on a count of how many times the suggested query candidate was previously selected.

16. The machine-readable volatile or non-volatile medium of claim 14, wherein the attribute is a monetization value that reflects a monetary value that is associated with the suggested query candidate.

17. The machine-readable volatile or non-volatile medium of claim 14, instructions which, when executed by one or more processors, cause the one or more processors to further perform:

determining the suggested query candidates based, at least in part, on a count of how many times the suggested query candidates have been received from users.

18. The machine-readable volatile or non-volatile medium of claim 14, wherein the suggested queries comprise at least one of:

a) a predictive search query wherein a predictive search query is determined by predicting what the search query will be when completed;

or

b) an alternative search query wherein an alternative search query differs from the predicted search query and is determined based on the predicted search query.

19. The machine-readable volatile or non-volatile medium as recited in claim 14, wherein the attribute is information associated with a user that submitted the user search query.

20. The machine-readable volatile or non-volatile medium as recited in claim 14, wherein the suggested queries comprise at least one of:

a) a predictive search query wherein a predictive search query is determined by predicting what the search query will be when completed;

or

b) an alternative search query wherein an alternative search query differs from the predicted search query and is determined based on the predicted search query.

21. The machine-readable volatile or non-volatile medium as recited in claim 14, wherein a set of pre-defined search queries are formed prior to receiving the not-yet-submitted user search query.

22. The machine-readable volatile or non-volatile medium as recited in claim 21, wherein the step of generating a biased parameter is performed prior to receiving a not-yet-submitted user search query;

and

wherein the biased parameter is associated with a pre-defined search query of the set of pre-defined search queries.

23. The machine-readable volatile or non-volatile medium as recited in claim 14, wherein at least one suggested query candidate is selected by performing:

determining the current date;

determining an event taking place within a certain time window from the current date;

in response to determining, generating a suggested query term containing said event.

24. The machine-readable volatile or non-volatile medium as recited in claim 14, wherein generating a set of suggested query candidates is based on previous queries issued by at least one user other than said user;

wherein said previous queries are associated with a country of origin; and

selecting one or more suggested query candidates of the set of suggested query candidates gives a bias to query candidates that have the same country of origin as said user.

25. The machine-readable volatile or non-volatile medium as recited in claim 14, wherein the search initiation criteria is determined by setting a timer when the user enters a character in the not-yet submitted user search query, and the search initiation criteria are only met when the timer expires.