Abstract: System and methods for presenting users with different App download options in response to certain search queries. In aspects, when a user enters a search query that does not explicitly request an App, systems and methods described herein analyze the results of the search and determine whether the request is an implicit request for Apps. As a result, relevant Apps are identified and presented for download. Other aspects of the present disclosure relate to analyzing and identifying URLs of companies and developers of Apps. Once analyzed and identified, embodiments relate to associating the appropriate URLs with one or more Apps.

Abstract: A system and method of generating and using key-value clusters to classify and return app queries is provided. The system includes a computing device. The computing device includes: a processing device; and a computer readable data storage device storing instructions. When the instructions are executed by the processing device, the instructions are operative to provide: receiving a search query and retrieving a preliminary search result comprising at least n web results; and when the at least n web results matches the key cluster returning the key cluster and an associated value cluster as a result of the search.

Abstract: A market out of multiple available geographic markets can be inferred for each application in a first subset of computer applications. The inferring can include inferring each market from text in one or more metadata fields in application metadata from an online computerized store for the applications. Computer-readable market clusters can be generated, with each of the market clusters indicating a corresponding one of the markets, and with the clusters indicating an inferred market cluster of the computer-readable market clusters for each of the applications in the first subset. In response to a received application query, generating search results can include favoring inclusion of the one or more applications that are assigned to the identified market cluster relative to one or more applications that are not assigned to the identified market cluster.

Abstract: A plurality of category application queries can be processed, including identifying an associated list of results for each of the category application queries, with each list of results listing one or more applications. A cluster of the category application queries that each have a category in common in an application category stamp can be identified. A proximity graph for the category application queries in the cluster can be generated. The proximity graph can indicate similarity scores based at least in part on numbers of applications in common for lists of results associated with the category application queries in pairs of queries in the cluster. Lists each having one or more suggested alternative category application queries for category application queries in the cluster can be generated, with the generating of the lists of one or more suggested alternative category application queries being based at least in part on the similarity scores.

Abstract: Application metadata for computer applications can be retrieved, with the metadata corresponding to metadata for an online application store from which the applications are available. Computer-readable application clusters can be generated. Each of the application clusters can indicate that applications in the cluster are supported by an associated set of one or more platforms for the cluster. The generating of the clusters can include analyzing the application metadata, such as by performing pattern matching on natural language data. Results for application queries for applications supported by a specified computer platform can be limited to listings of applications in one or more of the clusters whose associated set of one or more platforms includes the specified platform.

Abstract: A limited first set of search engine results can be retrieved from running an application query, with the limited first set of results being limited to applications associated with a first set of application platform(s). Categories of applications referenced in the limited first set of results can be identified, and a category stamp can be generated for the query based on applications in the first set of results that are associated with each of multiple categories. A limited second set of search engine results can be retrieved from running the query. The limited second set of results can be limited to applications associated with a second set of application platform(s), with the second set of results being limited to applications in a category corresponding to the category stamp for the query. An application list for the query can be generated using the limited second set of results.

Abstract: A market out of multiple available geographic markets can be inferred for each application in a first subset of computer applications. The inferring can include inferring each market from text in one or more metadata fields in application metadata from an online computerized store for the applications. Computer-readable market clusters can be generated, with each of the market clusters indicating a corresponding one of the markets, and with the clusters indicating an inferred market cluster of the computer-readable market clusters for each of the applications in the first subset. In response to a received application query, generating search results can include favoring inclusion of the one or more applications that are assigned to the identified market cluster relative to one or more applications that are not assigned to the identified market cluster.

Abstract: A system and method of generating and using key-value clusters to classify and return app queries is provided. The system includes a computing device. The computing device includes: a processing device; and a computer readable data storage device storing instructions. When the instructions are executed by the processing device, the instructions are operative to provide: receiving a search query and retrieving a preliminary search result comprising at least n web results; and when the at least n web results matches the key cluster returning the key cluster and an associated value cluster as a result of the search.

Abstract: System and methods for presenting users with different App download options in response to certain search queries. In aspects, when a user enters a search query that does not explicitly request an App, systems and methods described herein analyze the results of the search and determine whether the request is an implicit request for Apps. As a result, relevant Apps are identified and presented for download. Other aspects of the present disclosure relate to analyzing and identifying URLs of companies and developers of Apps. Once analyzed and identified, embodiments relate to associating the appropriate URLs with one or more Apps.

Abstract: Application metadata for computer applications can be retrieved, with the metadata corresponding to metadata for an online application store from which the applications are available. Computer-readable application clusters can be generated. Each of the application clusters can indicate that applications in the cluster are supported by an associated set of one or more platforms for the cluster. The generating of the clusters can include analyzing the application metadata, such as by performing pattern matching on natural language data. Results for application queries for applications supported by a specified computer platform can be limited to listings of applications in one or more of the clusters whose associated set of one or more platforms includes the specified platform.

Abstract: A plurality of category application queries can be processed, including identifying an associated list of results for each of the category application queries, with each list of results listing one or more applications. A cluster of the category application queries that each have a category in common in an application category stamp can be identified. A proximity graph for the category application queries in the cluster can be generated. The proximity graph can indicate similarity scores based at least in part on numbers of applications in common for lists of results associated with the category application queries in pairs of queries in the cluster. Lists each having one or more suggested alternative category application queries for category application queries in the cluster can be generated, with the generating of the lists of one or more suggested alternative category application queries being based at least in part on the similarity scores.

Abstract: A limited first set of search engine results can be retrieved from running an application query, with the limited first set of results being limited to applications associated with a first set of application platform(s). Categories of applications referenced in the limited first set of results can be identified, and a category stamp can be generated for the query based on applications in the first set of results that are associated with each of multiple categories. A limited second set of search engine results can be retrieved from running the query. The limited second set of results can be limited to applications associated with a second set of application platform(s), with the second set of results being limited to applications in a category corresponding to the category stamp for the query. An application list for the query can be generated using the limited second set of results.

Abstract: A/B experiment validation implementations are presented that generally validate an A/B experiment prior to its release. One implementation involves employing multiple test execution engines to test a A/B experiment, and then aggregating the results. More particularly, a request to validate an A/B experiment is received from a requesting entity along with data pertaining to the A/B experiment. A category of the A/B experiment is then determined, and test execution engines applicable to the A/B experiment category are identified. For each test execution engine identified, the A/B experiment data is passed to the test execution engine, the test execution engine is requested to execute a test for the A/B experiment, and test results from the test of the A/B experiment are received. Once test results are received from the identified test execution engines, the test results are aggregated to produce a validation indicator.