Abstract: A current user lifecycle phase and a desired outcome for a user for a current user lifecycle phase are identified. Messages eligible to be shown to the user are identified based upon the current user lifecycle phase for the user. From the eligible messages, particular messages can be selected for delivery to the user based upon one or more governance rules, user attributes, user activity, seasonality, and/or the desired outcome for the current user lifecycle phase for the user. The selected messages can then be shown to the user. In this manner, relevant messages can be presented to the relevant users at a relevant time.

Abstract: A computer-implemented technique is described for generating a textual narrative based on a set of input images. In one scenario, the end user captures the set of input images while visiting one or more locations. The generated narrative describes the user's travel experience at those locations in a cohesive manner. In one implementation, the technique generates the narrative based on information extracted in offline fashion by a knowledge acquisition component. The knowledge acquisition component, in turn, produces the knowledgebase by mining one or more knowledge sources (such as one or more travel blogs) that provide image-annotated textual travel narratives. The technique can therefore be said to reuse common elements in the travel narratives of others in describing the user's own set of input images.

Abstract: Data is stored that defines a user lifecycle phase and a desired outcome for the user lifecycle phase. Metrics are computed for evaluating the individual effectiveness of each of the messages in a set of messages. Personalization rules can be generated for a particular user that are based on the computed metrics and attributes associated with the particular user. The personalization rules are rules for selecting messages from the set of messages for presentation to the particular user. The personalization rules can be provided to a computing device associated with the particular user. The computing device can utilize the personalization rules to select a message from the set of messages and present the selected message to the user.

Abstract: A current user lifecycle phase and a desired outcome for a user for a current user lifecycle phase are identified. Messages eligible to be shown to the user are identified based upon the current user lifecycle phase for the user. From the eligible messages, particular messages can be selected for delivery to the user based upon one or more governance rules, user attributes, user activity, seasonality, and/or the desired outcome for the current user lifecycle phase for the user. The selected messages can then be shown to the user. In this manner, relevant messages can be presented to the relevant users at a relevant time.

Abstract: A computer-implemented technique is described for generating a textual narrative based on a set of input images. In one scenario, the end user captures the set of input images while visiting one or more locations. The generated narrative describes the user's travel experience at those locations in a cohesive manner. In one implementation, the technique generates the narrative based on information extracted in offline fashion by a knowledge acquisition component. The knowledge acquisition component, in turn, produces the knowledgebase by mining one or more knowledge sources (such as one or more travel blogs) that provide image-annotated textual travel narratives. The technique can therefore be said to reuse common elements in the travel narratives of others in describing the user's own set of input images.

Abstract: A computer-implemented technique is described for generating a textual narrative based on a set of input images. In one scenario, the end user captures the set of input images while visiting one or more locations. The generated narrative describes the user's travel experience at those locations in a cohesive manner. In one implementation, the technique generates the narrative based on information extracted in offline fashion by a knowledge acquisition component. The knowledge acquisition component, in turn, produces the knowledgebase by mining one or more knowledge sources (such as one or more travel blogs) that provide image-annotated textual travel narratives. The technique can therefore be said to reuse common elements in the travel narratives of others in describing the user's own set of input images.

Abstract: A computer-implemented technique is described for generating a textual narrative based on a set of input images. In one scenario, the end user captures the set of input images while visiting one or more locations. The generated narrative describes the user's travel experience at those locations in a cohesive manner. In one implementation, the technique generates the narrative based on information extracted in offline fashion by a knowledge acquisition component. The knowledge acquisition component, in turn, produces the knowledgebase by mining one or more knowledge sources (such as one or more travel blogs) that provide image-annotated textual travel narratives. The technique can therefore be said to reuse common elements in the travel narratives of others in describing the user's own set of input images.