Performing application searches

• US 10,180,967 B2
• Filed: 07/29/2015
• Issued: 01/15/2019
• Est. Priority Date: 04/27/2012
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd. (Samsung Group)
• Original Assignee: Samsung Electronics Co. Ltd. (Samsung Group)
• Inventors: Glover, Eric, Shapira, Liron, Tarleton, Nicolas
• Primary Examiner(s): Ortiz Ditren, Belix M
• Application Number:
  US14/812,314
• Publication Number:
  US 20150347420A1
• Time in Patent Office: 1,266 Days
• Field of Search: None
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/31 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/90 Details of database functions independent of the retrieved data types
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

According to some implementations, a technique for processing an application search query is disclosed. The techniques include receiving a search query from a partner, determining a set of subqueries based on the search query, and extracting query features of the search query from the search query. The techniques further include determining an initial result set of applications based on the set of subqueries and the query features. The initial result set includes a plurality of application representations each defining features of a different application. The techniques also include determining a score for each application in the initial result set of applications based on the set of query features and one or more scoring models, determining a result set based on the scores of the applications in the initial result set, and providing the result set to the partner.

Claims

1. A method comprising:

receiving, by a processing device, a search query from a partner device via a network;

extracting, by the processing device, one or more query features of the search query from the search query;

identifying, by the processing device, a consideration set of application representations based on the search query and a search index that indexes a plurality of application representations, each application representation being a data structure representing a different application and defining features of the application and editions of the application, the features of the application and editions of the application being extracted from one or more documents obtained from one or more respective sources separate from the application, and each document relating to the application;

determining, by the processing device, a score for each application representation in the consideration set of application representations based on the one or more query features of the search query and one or more machine-learned scoring models;

determining, by the processing device, a ranked result set based on the scores of the application representations, the ranked result set indicating one or more applications that correspond to the search query; and

transmitting, by the processing device, the ranked result set to the partner device via the network.

2. The method of claim 1, wherein identifying the consideration set of application representations includes:

identifying a pre-consideration set of application representations from the search index by querying the search index using the search query; and

reducing the pre-consideration set of application representations into the consideration set of application representations based on a subset of features defined in the application representations of the pre-consideration set of application representations.

3. The method of claim 2, wherein identifying the pre-consideration set of application representations includes:

generating a set of sub-queries based on the search query and context data, the set of sub-queries representing different combinations of query terms in the search query and instances of information in the context data;

querying the search index with at least one of the set of sub-queries, the search index identifying any application representations that are relevant to the at least one of the set of sub-queries; and

including the identified application representations in the pre-consideration set of application representations.

4. The method of claim 1, wherein receiving the search query includes receiving a query wrapper containing the search query and context data indicating information related to the partner device.

5. The method of claim 4, wherein identifying the consideration set of application representations further includes:

generating a set of sub-queries based on the search query;

querying the search index with at least one of the set of sub-queries, the search index identifying any application representations that are relevant to the at least one of the set of sub-queries;

including the identified application representations in a pre-consideration set of application representations; and

reducing the pre-consideration set of application representations into the consideration set of application representations based on a subset of features defined in the application representations included in the pre-consideration set of application representations.

6. The method of claim 1, wherein determining the score for each application representation in the consideration set of application representations includes:

determining one or more query/result features of the application representation, each query/result feature defining a feature of the application representation with respect to the search query; and

feeding at least a subset of the features of the application, the query/result features, and the query features to the one or more machine-learned scoring models.

7. The method of claim 1, wherein determining the ranked result set includes:

ranking the scored application representations based on the respective scores thereof; and

selecting one or more of the ranked scored application representations for inclusion in the ranked result set based on the respective ranking of the ranked scored application representations.

8. The method of claim 1, wherein transmitting the ranked result set includes:

for each application representation indicated in the ranked result set;

obtaining display data corresponding to the application represented by the application representation, and

including the display data with the application representation.

9. The method of claim 1, wherein the partner device is a user device.

10. A search server comprising:

a storage device that stores;

a plurality of application representations, each application representation being a data structure representing a different application and including one or more features of the application and identifying one or more editions of the application, the one or more features of the application and editions of the application being extracted from one or more documents obtained from one or more respective sources separate from the application, each document relating to at least one edition of the application; and

a search index that indexes the plurality of application representations, the search index being keyed by a set of attributes that correspond to at least one of the applications represented by the application representations stored in the storage device;

a processing device that executes computer-readable instructions, the computer-executable instructions causing the processing device to;

receive a search query from a partner device via a network;

extract one or more query features of the search query from the search query;

identify a consideration set of application representations based on the search query and the search index;

determine a score for each application representation in the consideration set of application representations based on the one or more query features of the search query and one or more machine-learned scoring models;

determine a ranked result set based on the scores of the application representations, the ranked result set indicating one or more applications that correspond to the search query; and

transmit the ranked result set to the partner device via the network.

11. The search server of claim 10, wherein identifying the consideration set of application representations includes:

identifying a pre-consideration set of application representations from the search index by querying the search index using the search query; and

reducing the pre-consideration set of application representations into the consideration set of application representations based on a subset of features defined in the application representations of the pre-consideration set of application representations.

12. The search server of claim 11, wherein identifying the consideration set of application representations includes:

generating a set of sub-queries based on the search query and context data, the set of sub-queries representing different combinations of query terms in the search query and instances of information in the context data;

querying the search index with at least one of the set of sub-queries, the search index identifying any application representations that are relevant to the at least one of the set of sub-queries; and

including the identified application representations in the pre-consideration set of application representations.

13. The search server of claim 10, wherein receiving the search query includes receiving a query wrapper containing the search query and context data indicating information related to the partner device.

14. The search server of claim 13, wherein identifying the consideration set of application representations further includes:

generating a set of sub-queries based on the search query;

querying the search index with at least one of the set of sub-queries, the search index identifying any application representations that are relevant to the at least one of the set of sub-queries;

including the identified application representations in a pre-consideration set of application representations; and

reducing the pre-consideration set of application representations into the consideration set of application representations based on a subset of features defined in the application representations included in the pre-consideration set of application representations.

15. The search server of claim 10, wherein determining the score for each application representation in the consideration set of application representations includes:

determining one or more query/result features of the application representation, each query/result feature defining a feature of the application representation with respect to the search query; and

feeding at least a subset of the features of the application, the query/result features, and the query features to the one or more machine-learned scoring models.

16. The search server of claim 10, wherein determining the ranked result set includes:

ranking the scored application representations based on the respective scores thereof; and

selecting one or more of the ranked scored application representations for inclusion in the ranked result set based on the respective ranking of the ranked scored application representations.

17. The search server of claim 10, wherein transmitting the ranked result set includes:

for each application representation indicated in the ranked result set;

obtaining display data corresponding to the application represented by the application representation; and

including the display data with the application representation.

18. The search server of claim 10, wherein the partner device is a user device.