PERFORMING APPLICATION SEARCH BASED ON APPLICATION GAMINESS
An application search system compensates for game bias in search results using a gaminess value representing the likelihood that an application is a game. The application search system receives a gaminess value for an application from an external source, such as an operator, or automatically determines the gaminess value using a trained computer model. The computer model may be trained based on a supervised training set of data. The gaminess value of an application is used to determine relevance of applications responsive to a search query. In one configuration, the gaminess value is incorporated as a scoring feature by the application search system in a computer-learned relevance search. The gaminess value may be used as a relevance factor even when the search does not indicate a user's desire to search for a game.
1 . A computer program product for performing application search, the computer program product comprising a non-transitory computer-readable storage medium storing instructions that when executed cause at least one processor to perform steps comprising:
receiving data from one or more data sources for one or more applications;
determining one or more gaminess values for the one or more applications based at least in part on the received data, wherein a gaminess value indicates the likelihood that an application is a game;
receiving a search query including one or more search terms from a user device;
identifying a consideration set of applications based on the search query from the one or more applications;
generating a result score for each application in the identified set based at least in part on the gaminess value for the application in the identified set;
ranking the identified set of applications based on the relevancy score; and
providing a listing of the ranked set of applications to the user device.
2 . The computer program product of claim 1 , wherein a gaminess value for an application is a value selected from at least three different gaminess values.
3 . The computer program product of claim 1 , wherein the provided ranked set of applications includes at least one application that is a game and at least one other application that is not a game.
4 . The computer program product of claim 1 , wherein applications are excluded from the consideration set based on the gaminess value of the applications.
5 . The computer program product of claim 1 , wherein the result score is generated based on a set of scoring factors applied by a computer model, wherein the gaminess value is a scoring factor.
6 . The computer program product of claim 1 , wherein the result score for the application is generated based on a set of scoring factors applied by a computer model, wherein the gaminess value modifies the score result of the computer model.
7 . The computer program product of claim 6 , wherein a gaminess value above a threshold reduces or boosts the score result generated by the computer model.
8 . The computer program product of claim 6 , wherein a gaminess value below a threshold reduces or boosts the score result generated by the computer model.
9 . The computer program product of claim 1 , wherein the gaminess values for the one or more applications is determined based on a trained gaminess computer model.
10 . The computer program product of claim 9 , wherein the trained gaminess computer model is trained using a supervised training set.
11 . A computer-implemented method of generating search results for an application search query, comprising:
accessing, by a processor, an application data store including application records, each application record associated with an application and including a gaminess value indicating the likelihood that the application associated with the application record is a game;
receiving a search query including one or more search terms from a user device;
generating, by the processor, a result score for a plurality of applications based at least in part on the gaminess value associated with the applications in the associated application record.
12 . The computer-implemented method of claim 11 , further comprising training a computer model configured to receive scoring features describing an application and output a result score; wherein the scoring features including a gaminess value; and further wherein generating the result score comprises applying the computer model.
13 . The computer-implemented method of claim 11 , further comprising training a gaminess computer model to generate a gaminess value, using a training set of application data and target gaminess values, and further generating the gaminess value for an application record by applying the gaminess computer model.
14 . The computer-implemented method of claim 13 , wherein the target gaminess values are selected by a human operator.
15 . The computer-implemented method of claim 13 , wherein the target gaminess values are selected based on an average of gaminess selects by a plurality of human operators.
16 . The computer-implemented method of claim 13 , wherein the target gaminess values are selected based on a dictionary of terms.
17 . The computer-implemented method of claim 13 , wherein the target gaminess values are determined from a tag or label of the application at a data source or an application marketplace.
18 . A computer-implemented method of ordering search results for an application search query, comprising:
accessing, by a processor, an application data store including application records, each application record associated with an application and including a gaminess value indicating the likelihood that the application associated with the application record is a game;
receiving a search query including one or more search terms from a suer device;
generating, by the processor, one or more ranking features for a plurality of applications based at least in part on the gaminess value associated with the applications in the associated application record; and
organizing the consideration set results based on the ranking features.
19 . The computer-implemented method of claim 18 , wherein organizing the consideration set results comprises clustering the consideration set results based on the gaminess values associated with the applications in the consideration set.
20 . The computer-implemented method of claim 18 , wherein organizing the consideration set results comprises ranking the consideration set results based on the gaminess values associated with the applications in the consideration set.