Abstract: Systems and methods are provided that automatically process a message input, construct an intelligent query based on the processing of the message input, and provide at least one attachable entity according to the processing results and the intelligent query. In some example aspects, a message is received. A natural language processor to determine if the message is requesting content may then process the message. If the message is determined to be requesting content, then candidate sub-queries may be generated to serve as a training set for a query that will be sent to an external search engine to retrieve the attachable entity. The sub-queries may be ranked in order of relevance and performance score. The highest ranked sub-queries may then be used in the actual query that is fired against the external search engine. The external search engine may search local and remote repositories for the top K most relevant attachable entities and present them to a user for attachment in a reply message.

Abstract: A computer-implemented technique is described herein for creating a relational data structure by extracting user data items from a collection of one or more applications sources. These data items evince interests exhibited by the users, and may include messages, documents, tasks, meetings, etc. The technique also collects knowledge data items from one or more knowledge sources. In one implementation, these data items may include terms used to describe skills possessed by the users. The technique constructs the data structure by providing objects associated with respective data items, and links between respective pairs of objects. In its real-time phase of operation, the technique allows a user to interrogate the relational data structure, e.g., to identify skills possessed by a particular user, to find users associated with a specified skill, etc.

Abstract: A computer-implemented technique is described herein for creating a relational data structure by extracting user data items from a collection of one or more applications sources. These data items evince interests exhibited by the users, and may include messages, documents, tasks, meetings, etc. The technique also collects knowledge data items from one or more knowledge sources. In one implementation, these data items may include terms used to describe skills possessed by the users. The technique constructs the data structure by providing objects associated with respective data items, and links between respective pairs of objects. In its real-time phase of operation, the technique allows a user to interrogate the relational data structure, e.g., to identify skills possessed by a particular user, to find users associated with a specified skill, etc.

Abstract: Systems and methods are provided that automatically process a message input, construct an intelligent query based on the processing of the message input, and provide at least one attachable entity according to the processing results and the intelligent query. In some example aspects, a message is received. A natural language processor to determine if the message is requesting content may then process the message. If the message is determined to be requesting content, then candidate sub-queries may be generated to serve as a training set for a query that will be sent to an external search engine to retrieve the attachable entity. The sub-queries may be ranked in order of relevance and performance score. The highest ranked sub-queries may then be used in the actual query that is fired against the external search engine. The external search engine may search local and remote repositories for the top K most relevant attachable entities and present them to a user for attachment in a reply message.

Abstract: Various technologies pertaining to assigning metadata to images in a personal image collection of a user based upon images and associated metadata assigned thereto that are accessible to the user by way of a social network application are described. An account of the user in a social network application is accessed to retrieve images and metadata that is accessible to the user. A face recognition algorithm is trained based upon the retrieved images and metadata, and the trained face recognition algorithm is executed over the personal image collection of the user, where the personal image collection of the user is external to the social network application.

Abstract: Described are techniques for capturing and analyzing snapshots of virtual machines. One or more computers may automatically obtain snapshots of virtual machines as they are executing to form a pool of virtual machine snapshots. The virtual machine snapshots are then read to obtain a set of features properties of the virtual machine snapshots, including information about a running guest operating system, software installed on the virtual machine, metadata about the virtual machine itself, and others. The features or properties are analyzed, in one embodiment using a machine learning algorithm, to automatically compute and store information about the virtual machines.

Abstract: Various technologies pertaining to assigning metadata to images in a personal image collection of a user based upon images and associated metadata assigned thereto that are accessible to the user by way of a social network application are described. An account of the user in a social network application is accessed to retrieve images and metadata that is accessible to the user. A face recognition algorithm is trained based upon the retrieved images and metadata, and the trained face recognition algorithm is executed over the personal image collection of the user, where the personal image collection of the user is external to the social network application.

Abstract: Described are techniques for capturing and analyzing snapshots of virtual machines. One or more computers may automatically obtain snapshots of virtual machines as they are executing to form a pool of virtual machine snapshots. The virtual machine snapshots are then read to obtain a set of features properties of the virtual machine snapshots, including information about a running guest operating system, software installed on the virtual machine, metadata about the virtual machine itself, and others. The features or properties are analyzed, in one embodiment using a machine learning algorithm, to automatically compute and store information about the virtual machines.

Abstract: A master image can be generated based upon evaluation of virtual machine images. The master image includes single instances of data segments that are shared across virtual machine images within a virtual machine environment. The master image can be further be constructed as a function of a peer pressure technique that includes data segments common to a majority of the virtual machine images within the master image. The data segments included within the master image can further be defined by prioritizing data within virtual machine images as well as identifying influential data with a peer pressure technique.

Abstract: A computing device has a file stored on a storage volume by a file system and accessed through such file system. The file is defined to include data and metadata relating to the data, and at least a portion of the data of the file is removed from the file and stored at an alternate location such that the data does not occupy substantially any space on the volume and the file is in a reduced, ghosted form. The ghosted file is reconstituted for use by retrieving the data from the alternate location and associating such retrieved data with such ghosted file to form the reconstituted file.

Abstract: A computing device has a storage volume, a file system managing the storage volume, and a file stored on the storage volume and accessed by such file system. The file system receives an open command for the file from an application, notes that the file has been ghosted in that data of the file has been moved to an alternate location, and returns an error. The returned error is intercepted and the file system is commanded to retrieve ghosting information from the ghosted file. A handle corresponding to the ghosted file is delivered to the application, and a read command for the file is received from the application, including the handle, an offset, and a read length. Reconstituting of the ghosted file is initiated based on the data thereof at the alternate location, and after reconstituting the read command is responded to with the data requested.

Abstract: Extensible device data gathering is performed by a server in concert with at least one gatherer. The server accepts requests from clients and dispatches a gatherer to gather device data from devices on a network. When the data is returned, the server stores the data in a repository. The server also handles requests for repository data from clients. A gatherer presents an interface to the server which the server can use to dispatch the gatherer. The system is extensible because new gatherers may be created and may register with the server without any changes to the server. In one embodiment, this extensibility is achieved using the COM (Component Object Model) technology.

Abstract: A globally unique device identification is created. Initially, for a device, polling is performed for information regarding certain hardware components, such as hard disks, network cards, sound cards, video cards, etc. A device identifier is assigned to the device, which in one embodiment, is based on the hardware component information. The device identifier and the current information regarding the hardware components of the system are stored in a repository. Periodically, a new poll is performed of the hardware components of the system, and the current hardware component information in the repository is updated. A device is identified by the identity or similarity of the hardware component information read from the device with the stored current hardware component information.

Abstract: Aspects of the subject matter described herein relate to replicating initial content in resource replication systems. In aspects, each member participating in a replica group obtains a content set state from a directory service. The content set state indicates whether the member is allowed to synchronize resources with another member participating in the replica group. If the member is designated as a primary member, the member may replicate out resources to its downstream partners. If a member is not designated as a primary member, the member may not replicate out resources to its downstream partners until it has successfully synchronized resources with an upstream partner. Fence values may be set which control which resources win (and are replicated out) during synchronization.

Abstract: Aspects of the subject matter described herein relate to replicating resources across machines participating in a replica set. In aspects, a downstream machine requests that an upstream machine notify the downstream machine when updates to resources of the replica set occur. When such updates occur, the upstream machine notifies the downstream machine. In response thereto, the downstream machine requests resource meta-data and may include a limit as to how much resource meta-data may be sent. The upstream machine responds with the requested resource meta-data. Thereafter, the downstream machine determines which data associated with the updated resources to request and requests such data.

Abstract: A computing device has a file stored on a storage volume by a file system and accessed through such file system. The file is defined to include data and metadata relating to the data, and at least a portion of the data of the file is removed from the file and stored at an alternate location such that the data does not occupy substantially any space on the volume and the file is in a reduced, ghosted form. The ghosted file is reconstituted for use by retrieving the data from the alternate location and associating such retrieved data with such ghosted file to form the reconstituted file.

Abstract: A computing device has a storage volume, a file system managing the storage volume, and a file stored on the storage volume and accessed by such file system. The file system receives an open command for the file from an application, notes that the file has been ghosted in that data of the file has been moved to an alternate location, and returns an error. The returned error is intercepted and the file system is commanded to retrieve ghosting information from the ghosted file. A handle corresponding to the ghosted file is delivered to the application, and a read command for the file is received from the application, including the handle, an offset, and a read length. Reconstituting of the ghosted file is initiated based on the data thereof at the alternate location, and after reconstituting the read command is responded to with the data requested.

Abstract: Extensible device data gathering is performed by a server in concert with at least one gatherer. The server accepts requests from clients and dispatches a gatherer to gather device data from devices on a network. When the data is returned, the server stores the data in a repository. The server also handles requests for repository data from clients. A gatherer presents an interface to the server which the server can use to dispatch the gatherer. The system is extensible because new gatherers may be created and may register with the server without any changes to the server. In one embodiment, this extensibility is achieved using the COM (Component Object Model) technology.

Abstract: A globally unique device identification is created. Initially, for a device, polling is performed for information regarding certain hardware components, such as hard disks, network cards, sound cards, video cards, etc. A device identifier is assigned to the device, which in one embodiment, is based on the hardware component information. The device identifier and the current information regarding the hardware components of the system are stored in a repository. Periodically, a new poll is performed of the hardware components of the system, and the current hardware component information in the repository is updated. A device is identified by the identity or similarity of the hardware component information read from the device with the stored current hardware component information.