Abstract: Systems and methods relating to an online system for allowing interactions between online users. The system continuously tracks each user's interactions with different types and categories of content as well as with other users. Based partially on each user's tracked interactions, a probability based model of preferences, interests, and needs is created for each user. The probability based model is then used to predict a user's compatibility with other users and to recommend content. Based on predicted compatibilities, communities and groups of users are recommended to each user. To account for changing user profiles, each user's profile is periodically assessed against the profiles of other users for compatibility. Similarities in interests, preferences, and needs between users, as well as peer rankings, are taken into account when assessing compatibility between users and user groups and communities.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating configuration files using executable template language statements. One of the methods includes receiving a configuration template file for a structured configuration language that defines nodes, relationships between nodes, and, for each of one or more nodes, associates metadata with the node. A reserved character pattern is identified in the configuration template file attached to text that defines a node in the structured configuration language, wherein the reserved character pattern has one or more associated statements in an executable template language. A graph representation is generated that includes the node corresponding to the text. Statements in the executable template language associated with the reserved character pattern are executed to generate associated metadata for the node.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating configuration files using executable template language statements. One of the methods includes receiving a configuration template file for a structured configuration language that defines nodes, relationships between nodes, and, for each of one or more nodes, associates metadata with the node. A reserved character pattern is identified in the configuration template file attached to text that defines a node in the structured configuration language, wherein the reserved character pattern has one or more associated statements in an executable template language. A graph representation is generated that includes the node corresponding to the text. Statements in the executable template language associated with the reserved character pattern are executed to generate associated metadata for the node.

Abstract: A distributed component software system that includes an analysis server that: (i) receives a set of messages, where each message is sent between components of a distributed component software system (DCSS), and where each message includes an identification of a respective source component, an identification of a respective target component and respective message content; (ii) for each message of the set of received messages, resolves the respective source component; (iii) for each message of the set of received messages, resolves the respective source component; (iv) determines a sequence of the plurality of messages; and (v) generates a human-understandable abstract corresponding to the set of received messages based upon the respective message sources, the respective message targets, the respective message content and the sequence of the set of received messages.

Abstract: A distributed component software system that includes an analysis server that: (i) receives a set of messages, where each message is sent between components of a distributed component software system (DCSS), and where each message includes an identification of a respective source component, an identification of a respective target component and respective message content; (ii) for each message of the set of received messages, resolves the respective source component; (iii) for each message of the set of received messages, resolves the respective source component; (iv) determines a sequence of the plurality of messages; and (v) generates a human-understandable abstract corresponding to the set of received messages based upon the respective message sources, the respective message targets, the respective message content and the sequence of the set of received messages.