Adjusting Result Rankings For Broad Queries

1 . A computer-implemented method, the method comprising:

receiving a current user query;

building a query graph for an electronic document based on user-submitted queries, each query comprising one or more query terms, wherein the query graph comprises queries in parent-child relationships, wherein each child query in the query graph represents a refinement of a respective parent query in the query graph;

for each of one or more of the queries in the query graph:

determining a respective mass of the query using a count of submissions of the query and a count of submissions of query refinements represented by each child of the query in the query graph;

determining a respective match score of the query based on a correlation between the query and a portion of the electronic document; and

computing a respective weight of the query in reference to the electronic document based on the mass and the match score of the query;

selecting one or more parent-child relationships in the query graph based on the mass or the computed weight of a corresponding query in the query graph and a threshold value;

generating a query map based on the selected parent-child relationships;

identifying one or more child queries that have a corresponding parent query that matches the current user query;

submitting the identified one or more child queries to a search engine; and

providing for display a merged result set that includes search results of each of the submitted child queries.

2 . The method of claim 1 , further comprising:

identifying a plurality of queries in the query graph that contain identical query terms, each of the plurality of queries being a child query of a distinct parent query;

representing the plurality of queries as a single query; and

substituting the identified child query of each distinct parent query in the query graph with the single query.

3 . The method of claim 1 , wherein determining the match score comprises applying a formula as follows:

Sm ( Q,D )=( Ct/Lq+Ct/Ld )/2,

where Sm(Q, D) is the match score that measures the correlation between the query Q and the portion of the electronic document D, Ct is a number of terms that appear in both Q and D, Lq is a length of Q measured by a total number of terms in Q, and Ld is a length of the portion of the electronic document D.

4 . The method of claim 3 , wherein computing the weight W(Q, D) of the query Q in reference to the portion of the electronic document D comprises multiplying the match score Sm(Q, D) of the query Q by the mass of the query Q.

5 . The method of claim 1 , wherein computing the weight of the query in reference to the document further comprises:

multiplying a query count of the query by the match score of the query to produce the weight of the query, the query count comprising a number of times that the query has been submitted; and

for each descendent query of the query in the query graph:

multiplying a query count of the descendent query and a match score of the descendent query to produce a descendent query weight; and

adding the descendent query weight to the weight of the query.

6 . The method of claim 1 , wherein each submission of the query or query refinement that is counted is the submission of the query or query refinement to a search engine causing retrieval of one or more electronic documents.

7 . The method of claim 1 , further comprising:

adjusting a ranking of the electronic document as a search result for one of the submitted child queries based on the computed weight of the corresponding query in the query graph.

8 . A computer program product stored on a non-transitory computer storage medium, operable to cause data processing apparatus to perform operations comprising:

receiving a current user query;

building a query graph for an electronic document based on user-submitted queries, each query comprising one or more query terms, wherein the query graph comprises queries in parent-child relationships, wherein each child query in the query graph represents a refinement of a respective parent query in the query graph;

for each of one or more of the queries in the query graph:

determining a respective mass of the query using a count of submissions of the query and a count of submissions of query refinements represented by each child of the query in the query graph;

determining a respective match score of the query based on a correlation between the query and a portion of the electronic document; and

computing a respective weight of the query in reference to the electronic document based on the mass and the match score of the query;

selecting one or more parent-child relationships in the query graph based on the mass or the computed weight of a corresponding query in the query graph and a threshold value;

generating a query map based on the selected parent-child relationships;

identifying one or more child queries that have a corresponding parent query that matches the current user query;

submitting the identified one or more child queries to a search engine; and

providing for display a merged result set that includes search results of each of the submitted child queries.

9 . The computer program product of claim 8 , wherein the operations further comprise:

identifying a plurality of queries in the query graph that contain identical query terms, each of the plurality of queries being a child query of a distinct parent query;

representing the plurality of queries as a single query; and

substituting the identified child query of each distinct parent query with the single query.

10 . The computer program product of claim 8 , wherein determining the match score comprises applying a formula as follows:

Sm ( Q,D )=( Ct/Lq+Ct/Ld )/2,

wherein Sm(Q, D) is the match score that measures the correlation between the query Q and the portion of the electronic document D, Ct is a number of terms that appear in both Q and D, Lq is a length of Q measured by a total number of terms in Q, and Ld is a length of the portion of the electronic document D.

11 . The computer program product of claim 10 , wherein computing the weight W(Q, D) of the query Q in reference to the portion of the electronic document D comprises multiplying the match score Sm(Q, D) of the query Q by the mass of the query Q.

12 . The computer program product of claim 8 , wherein computing the weight of the query in reference to the document further comprises:

multiplying a query count of the query by the match score of the query to produce the weight of the query, the query count comprising a number of times that the query has been submitted; and

for each descendent query of the query in the query graph:

multiplying a query count of the descendent query and a match score of the descendent query to produce a descendent query weight; and

adding the descendent query weight to the weight of the query.

13 . The computer program product of claim 8 , wherein each submission of the query or query refinement that is counted is the submission of the query or query refinement to a search engine causing retrieval of one or more electronic documents.

14 . The computer program product of claim 8 , wherein the operations further comprise:

adjusting a ranking of the electronic document as a search result for one of the submitted child queries based on the computed weight of the corresponding query in the query graph.

15 . The computer program product of claim 8 , wherein adjusting the ranking of the electronic document further comprises:

filtering the query graph by excluding from the query graph queries whose weights do not exceed a threshold; and

increasing or decreasing the ranking of the electronic document according to the computed weight of the corresponding query in the filtered query graph.

16 . The computer program product of claim 8 , wherein filtering the query graph comprises:

calculating a score S(Q2, D) for each query Q2 in the query graph in reference to the portion of the electronic document D using a formula:

S ( Q 2, D )= W ( Q 2, D )/ M ( Q 2)− k/N ( Q 2),

wherein

W(Q2, D) is a weight of the query Q2 in reference to the portion of the electronic document D;

M(Q2) is a mass of the query Q2;

k is the threshold; and

N(Q2) is a number of child queries of the query Q2; and

excluding from the query graph queries whose scores are less than or equal to 0.

17 . A system comprising:

one or more computers configured to perform operations comprising:

receiving a current user query;

building a query graph for an electronic document based on user-submitted queries, each query comprising one or more query terms, wherein the query graph comprises queries in parent-child relationships, wherein each child query in the query graph represents a refinement of a respective parent query in the query graph;

for each of one or more of the queries in the query graph:

determining a respective mass of the query using a count of submissions of the query and a count of submissions of query refinements represented by each child of the query in the query graph;

determining a respective match score of the query based on a correlation between the query and a portion of the electronic document; and

computing a respective weight of the query in reference to the electronic document based on the mass and the match score of the query;

selecting one or more parent-child relationships in the query graph based on the mass or the computed weight of a corresponding query in the query graph and a threshold value;

generating a query map based on the selected parent-child relationships;

identifying one or more child queries that have a corresponding parent query that matches the current user query;

submitting the identified one or more child queries to a search engine; and

providing for display a merged result set that includes search results of each of the submitted child queries.

18 . The system of claim 17 , wherein the operations further comprise:

identifying a plurality of queries in the query graph that contain identical query terms, each of the plurality of queries being a child query of a distinct parent query;

representing the plurality of queries as a single query; and

substituting the identified child query of each distinct parent query in the query graph with the single query.

19 . The system of claim 17 , wherein determining the match score comprises applying a formula as follows:

Sm ( Q,D )=( Ct/Lq+Ct/Ld )/2,

wherein Sm(Q, D) is the match score that measures the correlation between the query Q and the portion of the electronic document D, Ct is a number of terms that appear in both Q and D, Lq is a length of Q measured by a total number of terms in Q, and Ld is a length of the portion of the electronic document D.

20 . The system of claim 19 , wherein computing the weight W(Q, D) of the query Q in reference to the portion of the electronic document D comprises multiplying the match score Sm(Q, D) of the query Q by the mass of the query Q.

21 . The system of claim 17 , wherein computing the weight of the query in reference to the document further comprises:

multiplying a query count of the query by the match score of the query to produce the weight of the query, the query count comprising a number of times that the query has been submitted; and

for each descendent query of the query in the query graph:

multiplying a query count of the descendent query and a match score of the descendent query to produce a descendent query weight; and

adding the descendent query weight to the weight of the query.

22 . The system of claim 17 , wherein each submission of the query or query refinement that is counted is the submission of the query or query refinement to a search engine causing retrieval of one or more electronic documents.

23 . The system of claim 17 , wherein the operations further comprise:

adjusting a ranking of the electronic document as a search result for one of the submitted child queries based on the computed weight of the corresponding query in the query graph.