Abstract: The systems and methods described herein provide for predictions of employee attrition within an enterprise. In one embodiment, the system connects to one or more internal data sources within the enterprise and one or more external data sources outside of the enterprise, receiving internal feed data from the internal data sources and external feed data from the external data sources, the internal feed data relating to a number of employees. The system then determines, based on at least the internal feed data, a number of attrition risk factors for the employees; receives LMS data corresponding to training courses being offered; generates one or more training course recommendations for the employees; and presents the training course recommendations to one or more client devices.

Abstract: Systems and methods describe providing for the dynamic prediction of employee attrition within an enterprise organization. The systems and methods involve connecting to internal data sources within the enterprise and external data sources outside of the enterprise; receiving internal and external feed data relating to a number of entities within the enterprise, including at least one or more employees of the enterprise; converting the internal and external feed data into normalized feed data within a single format; generating enterprise graphs based on the normalized feed data, with each enterprise graph representing relationships between entities within the enterprise at a point in time; generating a risk assessment model related to changes in the enterprise graphs over time; and providing to enterprise users, based on the risk assessment model, one or more attrition probabilities for at least a subset of the employees of the enterprise.

Abstract: There is provided a computer-implemented method for user query reformulation. A graph is created to represent a relationship between previous user query terms. The graph may represent the previous user searches in n-grams that correspond to nodes. A random walk analysis is performed to determine probabilities that various n-grams corresponding to nodes of the graph could be used to effectively alter a user search term. The probabilities represent a quantification of relationships between nodes of the graph. A determination may be made regarding whether to reformulate the user query based on a relationship between a user search term in the user query and a graphed search term represented by a node of the graph. The determination takes into account a relationship between the user search term and the graphed search term.

Abstract: There is provided a computer-implemented method for user query reformulation. A graph is created to represent a relationship between previous user query terms. The graph may represent the previous user searches in n-grams that correspond to nodes. A random walk analysis is performed to determine probabilities that various n-grams corresponding to nodes of the graph could be used to effectively alter a user search term. The probabilities represent a quantification of relationships between nodes of the graph. A determination may be made regarding whether to reformulate the user query based on a relationship between a user search term in the user query and a graphed search term represented by a node of the graph. The determination takes into account a relationship between the user search term and the graphed search term.