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: Systems, methods, and software are disclosed herein for implementing enhanced search environments. In one implementation, an enhanced service environment includes a working set service that receives event signals initiated by working set agents in various application services. The working set agents communicate the event signals to nominate events occurring in the application services for inclusion in a working set of information specific to a user. The nominations may be based at least in part on a working set model specific to the user. In response to receiving the event signals, the working set service determines which of the events qualify for inclusion in the working set of information based at least in part on the working set model. For each event that qualifies for inclusion, the working set is modified to include at least the event.

Abstract: A computer-implemented method that monitors the activity of different nodes within a system as well as crowd sourcing activity. The computer-implemented method determines that a first node formed a relationship with a second node, generates an edge based on the relationship between the first node and the second node, stores the edge in a graph index and assigns a privacy setting to the edge based on the relationship between the first and second nodes.

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 computer-implemented method that monitors the activity of different nodes within a system as well as crowd sourcing activity. The computer-implemented method determines that a first node formed a relationship with a second node, generates an edge based on the relationship between the first node and the second node, stores the edge in a graph index and assigns a privacy setting to the edge based on the relationship between the first and second nodes.

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 enhanced search environments. In one implementation, an enhanced service environment includes a working set service that receives event signals initiated by working set agents in various application services. The working set agents communicate the event signals to nominate events occurring in the application services for inclusion in a working set of information specific to a user. The nominations may be based at least in part on a working set model specific to the user. In response to receiving the event signals, the working set service determines which of the events qualify for inclusion in the working set of information based at least in part on the working set model. For each event that qualifies for inclusion, the working set is modified to include at least the event.

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: Concepts and technologies are described herein for managing a search index. In accordance with the concepts and technologies disclosed herein, a search index can be hosted by a number of search nodes. The search engine can be configured to determine if a search node is unavailable, and if so, if data stored at the unavailable search node is to be replaced. If data stored at the unavailable search node is to be replaced, the search engine can identify sources for data to be used to replace the data at the unavailable search node. The search engine can issue instructions to the sources and/or the unavailable search node to copy the data from the sources to the unavailable node and/or to replace the data at the unavailable node with the data from the sources. Portions of the data can be copied from each of the sources to the unavailable node.

Abstract: Concepts and technologies are described herein for managing a search index. In accordance with the concepts and technologies disclosed herein, a search index can be hosted by a number of search nodes. The search engine can be configured to determine if a search node is unavailable, and if so, if data stored at the unavailable search node is to be replaced. If data stored at the unavailable search node is to be replaced, the search engine can identify sources for data to be used to replace the data at the unavailable search node. The search engine can issue instructions to the sources and/or the unavailable search node to copy the data from the sources to the unavailable node and/or to replace the data at the unavailable node with the data from the sources. Portions of the data can be copied from each of the sources to the unavailable node.

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.