Identifying query aspects

1. A method comprising:

receiving a query in a computer system, the computer system comprising one or more computers, the query including an entity;

parsing the query to extract the entity;

generating in the computer system a group of candidate aspects for the entity;

for each pair of one or more pairs of candidate aspects, calculating a similarity score for the pair based on identifying respective aspect sets of search results corresponding to respective queries of candidate aspects in the pair of candidate aspects and comparing search results in the aspect sets of search results;

modifying in the computer system the group of candidate aspects to generate a group of modified candidate aspects based on the similarity score for the candidate aspects, the modifying comprising

combining similar candidate aspects, and

grouping candidate aspects using one or more aspect classes each associated with one or more candidate aspects;

ranking in the computer system one or more modified candidate aspects in the group of modified candidate aspects based on a diversity score and a popularity score;

associating in the computer system one or more highest ranked modified candidate aspects with the entity;

receiving in the computer system one or more sets of search results; and

providing a presentation of the search results in response to the query, the presentation presenting the search results organized according to the modified candidate aspects associated with the entity.

2. The method of claim 1 , further comprising:

presenting a summary of information about an entity in accordance with an aspect.

3. The method of claim 1 , where the one or more sets of search results include a set of search results responsive to the query.

4. The method of claim 1 , where each of the one or more sets of search results correspond to a respective aspect associated with the entity.

5. A method comprising:

receiving data identifying an entity;

parsing the data to extract the entity;

generating in a computer system a group of candidate aspects for the entity, the computer system comprising one or more computers;

for each pair of one or more pairs of candidate aspects, calculating a similarity score for the pair based on identifying respective aspect sets of search results corresponding to respective queries of candidate aspects in the pair of candidate aspects and comparing search results in the aspect sets of search results;

modifying in the computer system the group of candidate aspects to generate a group of modified candidate aspects based on the similarity score for the candidate aspects, the modifying comprising

combining similar candidate aspects, and

grouping candidate aspects using one or more aspect classes each associated with one or more candidate aspects;

ranking in the computer system one or more modified candidate aspects in the group of modified candidate aspects based on a diversity score and a popularity score; and

storing an association of one or more of the highest ranked modified candidate aspects with the entity in a data storage device of the computer system.

6. The method of claim 5 , further comprising:

receiving a query including the entity;

identifying one or more aspects associated with the entity;

receiving search results responsive to the query; and

presenting the search results based on the identified aspects.

7. The method of claim 5 , further comprising:

receiving a query including the entity;

identifying one or more aspects associated with the entity;

receiving one or more sets of search results, each set corresponding to one of the identified aspects; and

presenting the search results based on the identified aspects.

8. The method of claim 5 , further comprising receiving data identifying one or more entity properties, where:

generating the group of candidate aspects includes using the one or more entity properties; and

the one or more highest ranked candidates aspects are associated with both the entity and the entity properties.

9. The method of claim 5 , further comprising:

associating the entity with a class, the class having one or more class members including the entity; and

where generating the group of candidate aspects includes generating candidate aspects corresponding to the entity and the class.

10. The method of claim 9 , where generating the group of candidate aspects includes:

analyzing one or more first user search histories to identify queries associated with the entity; and

analyzing one or more second user search histories to identify queries associated with a class member other than the entity.

11. The method of claim 5 , where each similarity score is an estimate of similarity between two candidate aspects.

12. The method of claim 11 , where combining candidate aspects based on the similarity scores further comprises:

using a graph partition algorithm to determine which aspects to combine.

13. The method of claim 5 , where the comparison of the sets of search results includes a comparison of titles and snippets of the search results in one of the sets of search results to titles and snippets of the search results in the other one of the sets of search results.

14. The method of claim 5 , where grouping candidate aspects using one or more aspect classes includes:

associating two or more candidate aspects with a respective aspect class; and

grouping two or more candidate aspects into a single modified candidate aspect based on their aspect classes.

15. The method of claim 5 , where ranking one or more modified candidate aspects based on a diversity score and a popularity score includes:

calculating a popularity score for each aspect;

ranking the aspect with the highest popularity score the highest; and

ranking the remaining aspects by repeating the following steps one or more times:

calculating a similarity score for each un-ranked aspect, where the similarity score compares the similarity of the un-ranked aspect to the ranked aspects; and

assigning the next-highest ranking to the aspect whose popularity score divided by its similarity score is the highest.

16. A system comprising:

a processor; and

a computer storage medium including instructions, which, when executed by the processor, cause the processor to perform operations comprising:

receiving a query including an entity;

parsing the query to extract the entity;

generating a group of candidate aspects for the entity;

for each pair of one or more pairs of candidate aspects, calculating a similarity score for the pair based on identifying respective aspect sets of search results corresponding to respective queries of candidate aspects in the pair of candidate aspects and comparing search results in the aspect sets of search results;

modifying the group of candidate aspects to generate a group of modified candidate aspects based on the similarity score for the candidate aspects, the modifying comprising

combining similar candidate aspects, and

grouping candidate aspects using one or more aspect classes each associated with one or more candidate aspects;

ranking one or more modified candidate aspects in the group of modified candidate aspects based on a diversity score and a popularity score;

associating one or more highest ranked modified candidate aspects with the entity;

receiving one or more sets of search results; and

providing a presentation of the search results in response to the query, the presentation presenting the search results organized according to the aspects associated with the entity.

17. The system of claim 16 , wherein the instructions further include instructions to cause the processor to perform an operation comprising:

presenting a summary of information about an entity in accordance with an aspect.

18. The system of claim 16 , where the one or more sets of search results include a set of search results responsive to the query.

19. The system of claim 16 , where each of the one or more sets of search results correspond to a respective aspect associated with the entity.