Abstract: An example system includes a recommendation module. The recommendation module may receive a recommendation request including a set of installed application identifiers and identify a set of candidate application groups including at least one matching candidate application identifier. For each candidate application group, the recommendation module may determine a recommendation score based on a number of matching candidate application identifiers included in the candidate application group that match at least one installed application identifier. The recommendation module may select a first candidate application group based on the recommendation scores and select at least one non-matching candidate application identifier from the first candidate application group that does not match any of the installed application identifiers, resulting in a set of recommended application identifiers.

Abstract: A system includes a data processing device, a memory, identifications of applications, and a privacy indication module. Each identification of the application has associated therewith a privacy indicator that indicating a degree of expected privacy of each of the corresponding applications. The privacy indication module is configured to control the data processing device to set each of the privacy indicators of each of the identifications of the applications and to provide at least one of the privacy indicators to control publication of information corresponding to at least one of the applications.

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.

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.

Abstract: A method includes performing a search of an application data store using a search query. The application data store includes application data for a plurality of software applications available from a software-application marketplace. The application data includes a set of application statistics for each software application. Each set of application statistics includes statistical data points over time. The application data also includes a set of market-wide statistics that is an aggregate of the sets of application statistics over time. The method further includes generating a list of software applications identified during the search. Additionally, the method includes generating a result score for each software application in the list based on a set of market-adjusted statistics associated with the software application.

Abstract: An application search system stores information describing device capabilities used by one or more applications. The device capabilities describe interfaces with hardware on the user device. The application search system identifies the application capabilities related to applications in any search results. One method that the application search system identifies application capabilities includes identifying function calls to device interfaces used by an application. The application search system may receive user-selected identification of a desired application capability from a search, from a user-selected entry or from a search term, among others. The application capability in a search may be used to score relevance of applications and increase relevance of applications matching the desired application capability.

Abstract: An application classifier classifies applications using latent semantic indexing (LSI) vectors of the applications. The application classifier uses a machine-learned model generated based on pairs of LSI vectors of positive and negative training sets of applications, where the positive training set includes applications within a desired category and the negative training set includes applications outside of the desired category. For a given application, the application classifier determines whether the application belongs to the desired category based on similarity of an LSI vector of the application and LSI vectors of positive and negative exemplar applications, as determined by the machine-learned model. If the LSI vector of the application is similar to an LSI vector of at least one positive exemplar application and not similar to an LSI vector of any of the negative exemplar applications, the application is determined to belong to the desired category.

Abstract: 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.

Abstract: A method to recreate an application (“app”) experience on a first device on a second device, includes identifying one or more existing apps on the first device; generating a query for one or more apps matching the existing apps; sending the query to an application search engine through an application programming interface (API); searching an application search engine for one or more matching applications; and returning a set of matching apps in response to the query using the API.

Abstract: One embodiment of a disclosed system, method, and computer readable storage medium provides dynamic filtering in application searches. Partner systems leverage search functionality of an application search system configured to perform searches for applications. In one embodiment, partner systems select application categories to be associated with search queries submitted to the application search system via the partners' websites. When users submit search queries to the application search system via a partner system, the users' queries are associated with the partner system's application category selection. Alternatively, the search queries may implicitly or explicitly specify an application category. In response to receiving the queries, the application search system returns search results from the selected application category.

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.

Abstract: Techniques are disclosed for maintaining a search index used to support application searches. The techniques include receiving application data from one or more data sources, identifying an application referenced in the application data. The techniques further include extracting a plurality of attributes corresponding to the application from the application data based on an application specific search schema. The techniques also include generating an application representation of the application based on the plurality of attributes and the application specific search schema. The techniques also include updating a search index with the application representation.

Abstract: Systems, methods, and computer-readable media for performing a user search query are provided. A search definition profile having one or more domain constraints and one or more vertical constraints, specified by a site owner, is obtained. A first search for documents is executed with the search query for a first search result. The first search result is constrained to documents in a search engine index that satisfy a collective domain constraint imposed by the one or more domain constraints. Without user intervention, a second search for documents is executed with the search query for a second search result when a relevance condition of the first search result, specified by the site owner, is not satisfied. The second search result is constrained to a collective vertical constraint imposed by the one or more vertical constraints. An output search result that is combination of the first and second search results is provided.

Abstract: A system and method for predicting if a query is a name is provided. The method begins by providing an input query. A name database, having a list of names, famous names and queries that are known to not be a name is searched to determine if the input query is a name, a famous name or not a name. If the query is not located in the name database, the query is processed through a “looks like a name” function to determine if the query is a name. Systems and methods for classifying word strings as names, not names, and famous names are also provided. Systems and methods for creating name databases are also provided.

Abstract: The invention provides a system and method for providing an output in response to a user reference query. A user reference query is received and an answer to the user reference query is determined. A unique entity identifier (EID) for the answer is determined and used to query a reference system to determine one or more reference elements, e.g. a reference summary, a picture, or a video, for example. The one or more reference elements and a text of the answer are provided to an output provider. The output provider combines the one or more reference elements and the answer text into a single output. In one exemplary configuration, the single output is a graphical user interface transmitted as an extensible markup language (XML) file, which integrates the answer text and the one or more reference elements.

Abstract: According to one aspect of the invention, a method for managing the navigation of a visitor to the World Wide Web is provided. A target profile is determined based on a combination of at least two known properties and a navigation path is associated with the target profile. The at least two known properties are related to the at least one of a query, world knowledge, and information about a visitor to the World Wide Web. The visitor may be automatically directed along the navigation path.

Abstract: Systems and methods are disclosed to search for data responsive to first and second query concepts by generating a first expanded set of results from the first query concept; generating a second expanded set of results from the second query concept; determining an intersecting set of documents from the first and second expanded sets of results; and determining an explanation of a relationship for each document in the intersecting set of documents for each of the first and second query concepts.

Abstract: The present invention is directed to mechanisms for improving the “crawling” of resources on a network, which takes into account the notion of browser state. An improved indexing scheme for the crawled results and improved search mechanisms are also disclosed.

Abstract: Systems and methods are disclosed for analyzing a set of documents by building a positive set histogram; selecting phrases from the positive set histogram; modifying the frequency statistics in the histogram using the selected phrases; identifying one or more potential phrase-acronym pairs; selecting a subset of phrase-acronym pairs from the potential pairs; adding a new feature for each selected phrase-acronym (phrase ? acronym) pair to a positive set histogram; determining a value for each new feature; identifying one or more child concepts based on an updated histogram; grouping the one or more child concepts; and determining a child concept group coverage for one or more documents.

Abstract: A selective retrieval metasearch engine uses relevance estimation and confidence computation to select documents for which additional information is to be obtained. The additional information is used to update relevance estimation for the selected documents. A selective retrieval metasearch engine improves execution time, resource usage, throughput, and/or result quality.