Abstract: A graph query is executed against a graph index that connects actors with objects through edges. A graph ranking model is obtained and results of the graph query are ranked, using the graph ranking model, based upon edge data available from edges in the graph that match the query.

Abstract: A graph query is executed against a graph index that connects actors with objects through edges. A graph ranking model is obtained and results of the graph query are ranked, using the graph ranking model, based upon edge data available from edges in the graph that match the query.

Abstract: This disclosure describes methods and systems for searching documents in a multi-tenant hosting environment. According to embodiments, to conserve hardware resources, a plurality of documents associated with a plurality of tenants may be mapped to the same search index in the multi-tenant hosting environment. In order to search documents associated only with a single tenant in the multi-tenant hosting environment, a tenant identifier is prepended to every key stored in the search index that is associated with the plurality of documents of the single tenant. Moreover, where one document links to another document within the multi-tenant hosting environment, the link is stored in a web graph when a source tenant identifier matches a target tenant identifier for the link. According to embodiments, when conducting a search, the link is resolved only if the link is stored in the web graph.

Abstract: This disclosure describes methods and systems for searching documents in a multi-tenant hosting environment. According to embodiments, to conserve hardware resources, a plurality of documents associated with a plurality of tenants may be mapped to the same search index in the multi-tenant hosting environment. In order to search documents associated only with a single tenant in the multi-tenant hosting environment, a tenant identifier is prepended to every key stored in the search index that is associated with the plurality of documents of the single tenant. Moreover, where one document links to another document within the multi-tenant hosting environment, the link is stored in a web graph when a source tenant identifier matches a target tenant identifier for the link. According to embodiments, when conducting a search, the link is resolved only if the link is stored in the web graph.

Abstract: This disclosure describes methods and systems for searching documents in a multi-tenant hosting environment. According to embodiments, to conserve hardware resources, a plurality of documents associated with a plurality of tenants may be mapped to the same search index in the multi-tenant hosting environment. In order to search documents associated only with a single tenant in the multi-tenant hosting environment, a tenant identifier is prepended to every key stored in the search index that is associated with the plurality of documents of the single tenant. Moreover, where one document links to another document within the multi-tenant hosting environment, the link is stored in a web graph when a source tenant identifier matches a target tenant identifier for the link. According to embodiments, when conducting a search, the link is resolved only if the link is stored in the web graph.

Abstract: Systems, methods, and software are disclosed herein for implementing enterprise graph search. In at least one implementation, an enterprise search service receives a search request that includes a graph query directed to an enterprise graph. The graph is representative of various objects and actors associated with an enterprise, as well as which of the actors performed which of various actions with respect to each of the various objects. The service searches at least a portion of the enterprise graph to identify a subset of the objects that relate to the actors as defined by the graph query in terms of at least the actors and actions. A reply to the search request may include graph results indicative of the subset of the objects.

Abstract: Search results obtained from a ranking model are re-ranked based on user-configured ranking rules. For example, a user may desire to: place certain search results at a top/bottom of a ranking of search results; remove some search results; and/or adjust a ranking of some of the search results. A Graphical User Interface (GUI) allows a user to configure the ranking rules (e.g. enter key/value restrictions and to set a boost value) and to preview an application of one or more of the ranking rules. Query language operators that follow a standard operator syntax are created based on the inputs (e.g. a ranking query operator is created that may include multiple user supplied parameters). The user may also specify a portion of the results from which statistics (e.g. standard deviation, average score) are calculated. For example, a user may specify to calculate statistics for the top N number results.

Abstract: A graph query is executed against a graph index that connects actors with objects through edges. A graph ranking model is obtained and results of the graph query are ranked, using the graph ranking model, based upon edge data available from edges in the graph that match the query.

Abstract: Systems, methods, and software are disclosed herein for implementing enterprise graph search. In at least one implementation, an enterprise search service receives a search request that includes a graph query directed to an enterprise graph. The graph is representative of a various objects and actors associated with an enterprise, as well as which of the actors performed which of various actions with respect to each of the. The service searches at least a portion of the enterprise graph to identify a subset of the objects that relate to the actors as defined by the graph query in terms of at least the actors and actions. A reply to the search request may include graph results indicative of the subset of the objects.

Abstract: This disclosure describes methods and systems for searching documents in a multi-tenant hosting environment. According to embodiments, to conserve hardware resources, a plurality of documents associated with a plurality of tenants may be mapped to the same search index in the multi-tenant hosting environment. In order to search documents associated only with a single tenant in the multi-tenant hosting environment, a tenant identifier is prepended to every key stored in the search index that is associated with the plurality of documents of the single tenant. Moreover, where one document links to another document within the multi-tenant hosting environment, the link is stored in a web graph when a source tenant identifier matches a target tenant identifier for the link. According to embodiments, when conducting a search, the link is resolved only if the link is stored in the web graph.

Abstract: This disclosure describes methods and systems for searching documents in a multi-tenant hosting environment. According to embodiments, to conserve hardware resources, a plurality of documents associated with a plurality of tenants may be mapped to the same search index in the multi-tenant hosting environment. In order to search documents associated only with a single tenant in the multi-tenant hosting environment, a tenant identifier is prepended to every key stored in the search index that is associated with the plurality of documents of the single tenant. Moreover, where one document links to another document within the multi-tenant hosting environment, the link is stored in a web graph when a source tenant identifier matches a target tenant identifier for the link. According to embodiments, when conducting a search, the link is resolved only if the link is stored in the web graph.

Abstract: Concepts and technologies are described herein for query ranking models. In accordance with the concepts and technologies disclosed herein, a search engine can be configured to expose a query ranking model object corresponding to a ranking function used by the search engine. A query application can be configured to obtain the query ranking model object and generate a query ranking model based upon the query ranking model object. The query ranking model can include one or more features and respective weights. The query application can generate a query and include data with the query identifying the query ranking model that is to be used to rank search results generated by the search engine. The query application also can be configured to manage query ranking models to allow creation, modification, and/or deletion of query ranking models as well as weights of features of the query ranking models.

Abstract: Search results obtained from a ranking model are re-ranked based on user-configured ranking rules. For example, a user may desire to: place certain search results at a top/bottom of a ranking of search results; remove some search results; and/or adjust a ranking of some of the search results. A Graphical User Interface (GUI) allows a user to configure the ranking rules (e.g. enter key/value restrictions and to set a boost value) and to preview an application of one or more of the ranking rules. Query language operators that follow a standard operator syntax are created based on the inputs (e.g. a ranking query operator is created that may include multiple user supplied parameters). The user may also specify a portion of the results from which statistics (e.g. standard deviation, average score) are calculated. For example, a user may specify to calculate statistics for the top N number results.

Abstract: Search ranking features are described that may be used by a search engine to rank items in a search result. Examples of such features include use of multiple linear ranking stages, use of BM25 and a full text index, use of a minimum span on ranking stages, pre-calculation of a plurality of ranking models, use of a dynamic rank, use of more than one BM25 definition per stage, date/time transformations, freshness transformations, raw value transformations, query property rank, social distance, and so on.

Abstract: This disclosure describes methods and systems for searching documents in a multi-tenant hosting environment. According to embodiments, to conserve hardware resources, a plurality of documents associated with a plurality of tenants may be mapped to the same search index in the multi-tenant hosting environment. In order to search documents associated only with a single tenant in the multi-tenant hosting environment, a tenant identifier is prepended to every key stored in the search index that is associated with the plurality of documents of the single tenant. Moreover, where one document links to another document within the multi-tenant hosting environment, the link is stored in a web graph when a source tenant identifier matches a target tenant identifier for the link. According to embodiments, when conducting a search, the link is resolved only if the link is stored in the web graph.

Abstract: A method for creating a search index is disclosed. A plurality of words found in one or more documents is identified. For each word of the plurality of words, one or more fields of the one or more documents in which the word can be found is identified. Using a computing device, a search index is created for each word of the plurality of words. The search index for each word of the plurality of words provides a mapping between the word and each occurrence of the word in each field of the one or more documents in which the word is found.