Abstract: An approach is provided for providing real-time controlled location privacy as the location evolves, and providing a user with alternate routes and applications depending on the level of desired location privacy. A location privacy platform determines at least one location associated with at least one device. The location privacy platform also processes and/or facilitates a processing of contextual information associated with the at least one location, the at least one device, one or more applications associated with the at least one device, or a combination thereof to determine one or more privacy metrics for the one or more applications with respect to the at least one location; wherein the one or more privacy metrics relate, at least in part, to an exposure of user data by the one or more applications at the at least one location.

Abstract: Methods and apparatuses are provided for validating crowdsourced location data. A validation platform causes, at least in part, a determination of location data reported by at least one user, at least one device associated with the at least one user, or a combination thereof. The validation platform processes, and/or facilitates a processing of personal detail information associated with the at least one user, the at least one device, or a combination thereof to cause, at least in part, a validation of the location data.

Abstract: An approach is provided for providing abstracted user models in accordance with one or more access policies. A model platform determines an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models. The model platform further causes, at least in part, a generation of one or more user models for the one or more abstraction levels. The model platform also causes, at least in part, a selection of at least one of the one or more user models for generating one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on one or more privacy policies, one or more security policies, or a combination thereof.

Abstract: An approach is provided for determining and utilizing geographical locations contextually relevant to a user. A contextually relevant location platform determines location-based data associated with a user and/or user device. The contextually relevant location platform determines stationary points based, at least in part, on the location-based data. The contextually relevant location platform determines context data associated with the stationary points. The contextually relevant location platform determines at least one location anchor based, at least in part, on the stationary points and the associated context data, wherein the at least one location anchor represents a bounded geographical area of contextual relevance to the user.

Abstract: Methods and apparatuses are provided for validating crowdsourced location data. A validation platform causes, at least in part, a determination of location data reported by at least one user, at least one device associated with the at least one user, or a combination thereof. The validation platform processes, and/or facilitates a processing of personal detail information associated with the at least one user, the at least one device, or a combination thereof to cause, at least in part, a validation of the location data.

Abstract: An approach is provided for providing real-time controlled location privacy as the location evolves, and providing a user with alternate routes and applications depending on the level of desired location privacy. A location privacy platform determines at least one location associated with at least one device. The location privacy platform also processes and/or facilitates a processing of contextual information associated with the at least one location, the at least one device, one or more applications associated with the at least one device, or a combination thereof to determine one or more privacy metrics for the one or more applications with respect to the at least one location; wherein the one or more privacy metrics relate, at least in part, to an exposure of user data by the one or more applications at the at least one location.

Abstract: An approach is provided for providing intelligent processing of contextual information. An context platform determines at least one feature based, at least in part, on one or more contextual parameters The context platform further processes one or more contextual records to determine whether the at least one feature is a feature anchor based, at least in part, on whether the at least feature is represented above at least one threshold level. The context platform also processes the one or more contextual records to determine at least one profile for the at least one feature anchor.

Abstract: An approach is provided for providing abstracted user models in accordance with one or more access policies. A model platform determines an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models. The model platform further causes, at least in part, a generation of one or more user models for the one or more abstraction levels. The model platform also causes, at least in part, a selection of at least one of the one or more user models for generating one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on one or more privacy policies, one or more security policies, or a combination thereof.

Abstract: An approach is provided for recommendations based on locally generated models. The model platform causes, at least in part, a transfer of at least one user model from a device to a recommendation service, wherein the at least one user model is generated on the device. Next, the model platform determines to associate the at least one user model with user profile information. Then, the model platform processes and/or facilitates a processing of the at least one user model, the user profile information, or a combination thereof to generate at least one recommendation.

Abstract: An approach is provided for providing recommendations based on preloaded models and for generating user profiles to personalize a user experience with a device or service. A recommendation model platform processes at least one latent user model, at least one latent item model, or a combination thereof associated with a device to determine one or more user preference scores with respect to one or more items. The recommendation platform also processes the one or more user preference scores against one or more thresholds values to determine explicit preference information associated with the one or more items. The recommendation platform also generates at least one user profile associated with the device, a user of the device, or a combination thereof based, at least in part, on the explicit preference information.

Abstract: An approach is provided for determining and utilizing geographical locations contextually relevant to a user. A contextually relevant location platform determines location-based data associated with a user and/or user device. The contextually relevant location platform determines stationary points based, at least in part, on the location-based data. The contextually relevant location platform determines context data associated with the stationary points. The contextually relevant location platform determines at least one location anchor based, at least in part, on the stationary points and the associated context data, wherein the at least one location anchor represents a bounded geographical area of contextual relevance to the user.