Abstract: A most recently used (MRU) client synchronization engine is provided to synchronize a user's most recently used (MRU) document list associated with a client machine with a file hosting server's MRU document list. The file hosting server's MRU document list contains a list of the user's most recently used documents that are stored on the file hosting server. The user's documents that are stored on the file hosting server are accessible to the user on one or more web-enabled client machines. The MRU client synchronization engine analyzes registry data pertaining to the documents that a user uses on the client machine with the file hosting server's MRU document list to determine the user's most recently used documents.

Abstract: Faces may be indexed and identified using visual and social criteria. In one example, the visual features of a face are quantified, and the quantification of the features is represented in a vector. Aspects of the vector are then represented in the form of text strings. Social context surrounding the face is also represented in the form of text strings. The text strings—both the visual-based strings and/or the social-based strings—are associated with the face, and are stored in an index. The association of these strings with the face then may make the face text-searchable on both its visual and social features. Searches on these visual and/or social features may be used to help to assist in identifying new images of faces, or to propose tags for users to apply to photos.

Abstract: A most recently used (MRU) client synchronization engine is provided to synchronize a user's most recently used (MRU) document list associated with a client machine with a file hosting server's MRU document list. The file hosting server's MRU document list contains a list of the user's most recently used documents that are stored on the file hosting server. The user's documents that are stored on the file hosting server are accessible to the user on one or more web-enabled client machines. The MRU client synchronization engine analyzes registry data pertaining to the documents that a user uses on the client machine with the file hosting server's MRU document list to determine the user's most recently used documents.

Abstract: Faces may be indexed and identified using visual and social criteria. In one example, the visual features of a face are quantified, and the quantification of the features is represented in a vector. Aspects of the vector are then represented in the form of text strings. Social context surrounding the face is also represented in the form of text strings. The text strings—both the visual-based strings and/or the social-based strings—are associated with the face, and are stored in an index. The association of these strings with the face then may make the face text-searchable on both its visual and social features. Searches on these visual and/or social features may be used to help to assist in identifying new images of faces, or to propose tags for users to apply to photos.