Abstract: A method for creating and searching medical ontologies includes providing a semi-structured information source comprising a plurality of articles linked to each other, each article having one or more sections and each article is associated with a concept, creating a directed unlabeled graph representative of the information source, providing a plurality of labels, labeling a subset of edges, and assigning each unlabeled edge an equal probability of being assigned one of the labels. For each node, the probability of each outgoing edge is updated by smoothing each probability by an overall probability distribution of labels over all outgoing edges of each node, and the probability of each incoming edge is updated the same way. A label with a maximum probability is assigned to an edge if said maximum probability is greater than a predetermined threshold to create a labeled graph.

Abstract: A system, apparatus and application for providing robots with the ability to intelligently respond to perceived situations are described. A knowledge database is assembled automatically, based on distributed knowledge capture. The knowledge base embodies the “common sense,” that is, the consensus, of the subjects who contribute the knowledge. Systems are provided to automatically preprocess, or “clean” the information to make it more useful. The knowledge thus refined is utilized to construct a multidimensional semantic network, or MSN. The MSN provides a compact and efficient semantic representation suitable for extraction of knowledge for inference purposes and serves as the basis for task and response selection. When the robot perceives a situation that warrants a response, an appropriate subset of the MSN is extracted into a Bayes network. The resultant network is refined, and used to derive a set of response probabilities, which the robot uses to formulate a response.

Abstract: A method for creating and searching medical ontologies includes providing a semi-structured information source comprising a plurality of articles linked to each other, each article having one or more sections and each article is associated with a concept, creating a directed unlabeled graph representative of the information source, providing a plurality of labels, labeling a subset of edges, and assigning each unlabeled edge an equal probability of being assigned one of the labels. For each node, the probability of each outgoing edge is updated by smoothing each probability by an overall probability distribution of labels over all outgoing edges of each node, and the probability of each incoming edge is updated the same way. A label with a maximum probability is assigned to an edge if said maximum probability is greater than a predetermined threshold to create a labeled graph.

Abstract: A system and method for obtaining personal data about registered users using gaming principles is described. A data storage component receives and stores one or more items of personal data for each registered user. Multiple messages authored by multiple registered users are generated and displayed to a user interface for each registered user. The user interface provides a means for one registered user to select and categorize a message authored by another registered user. Based upon the nature of this categorized response, the responding user or seeker either gains or loses an item of personal data about author-user. Competition among users at different levels is introduced by applying a sorting process that limits the messages displayed to a particular user. In addition, resource management tools can be applied to limit author-user messages and seeker-user responses. Further, user actions and messages are scored and rankings are provided to all users.