Abstract: Techniques for identifying and viewing information items within an organization comprising a plurality of users each having one or more roles within the organization is disclosed. The disclosed techniques provide systems and methods for implementing and using a “skim preview” technique for previewing information items. This technique can be applied to a wide variety of information, such as presentations, documents, video, images, and so on and can be used for a variety of applications, including browsing, searching, discovery, and so on. The system can compute sequences that represent interesting visual aspects of the item being viewed. This can be applied to items that do not have a natural set of preview images, or it might be used as an alternative to the natural previews. The preview images may be sequenced chronologically, by importance, or based on any other metric.

Abstract: Techniques for organizing information, such as documents, presentations, web sites and web pages, audiovisual media streams, and the like are describe. This disclosed techniques include creating and using an interest graph to assist in a user's browsing of information. An interest graph expresses the affinity between people and information—the likelihood that a particular piece of information is of interest to a particular person. The interest graph is based on an understanding of relationships, monitoring of user behavior, and analysis of each piece of information. The interest graph represents many kinds of relationships, including: between users and other users, users and items, and users and collections. The interest graph can be computed using data both from a set of items and from user behavior.

Abstract: Techniques for organizing information, such as documents, presentations, web sites and web pages, audiovisual media streams, and the like are describe. This disclosed techniques include creating and using an interest graph to support the sharing of information via search, browsing, and discovery, etc. and measuring consumption, engagement, and/or influence based on that information. An interest graph expresses the affinity between people and information—the likelihood that a particular piece of information is of interest to a particular person. The interest graph is based on an understanding of relationships, monitoring of user behavior, and analysis of each piece of information. The interest graph represents many kinds of relationships, including: between users and other users, users and items, and users and collections. The interest graph can be computed using data both from a set of items and from user behavior.

Abstract: Techniques for organizing information, such as documents, presentations, web sites and web pages, audiovisual media streams, and the like are describe. This disclosed techniques include creating and using an interest graph to support the distribution of information to a user via a feed containing information items likely to be of interest to the user. An interest graph expresses the affinity between people and information—the likelihood that a particular piece of information is of interest to a particular person. The interest graph is based on an understanding of relationships, monitoring of user behavior, and analysis of each piece of information. The interest graph represents many kinds of relationships, including: between users and other users, users and items, and users and collections. The interest graph can be computed using data both from a set of items and from user behavior.

Abstract: A method, which identifies information of interest within an organization, determines use data that characterizes relationships among information items within the organization, where the information items include user data and collections of information items. The method generates interest data indicating affinities among the information items based on the determined use data. After receiving a query for data regarding the information items, the method responds to the query by providing one or more results based on the generated interest data. More details are provided herein.

Abstract: Abstracting communication with a plurality of containers. Each container encapsulates or hosts a module (e.g., a web service, a database, etc.) associated with a distributed application. A meta-container communicates with drivers that interface with each of the containers. The meta-container represents an abstraction and a virtualization of the containers in the hierarchy. Each container may also be a meta-container for other containers. The recursion and layered hierarchy provide flexible, extensible, and efficient management of the distributed application.

Abstract: Abstracting communication with a plurality of containers. Each container encapsulates or hosts a module (e.g., a web service, a database, etc.) associated with a distributed application. A meta-container communicates with drivers that interface with each of the containers. The meta-container represents an abstraction and a virtualization of the containers in the hierarchy. Each container may also be a meta-container for other containers. The recursion and layered hierarchy provide flexible, extensible, and efficient management of the distributed application.