Abstract: A platform for managing recommendation models is described. The platform processes and/or facilitates a processing of at least one user identification characteristic associated with at least one device to determine a user identity. The platform further determines at least one communication account active at the at least one device. The platform also causes, at least in part, an association of one or more recommendations models with the user identity, the at least one communication account, the at least one device, or a combination thereof.

Abstract: An apparatus providing for output of a content package may include a content category selector for receiving a content category selection. A content category extractor may extract the content category selection from a content feed. The apparatus may further comprise a contextual characteristic determiner for determining one or more contextual characteristics. A GPS module may determine a location of the apparatus. The apparatus may thereby provide for selection of a content package based at least in part on the content category selection and the one or more contextual characteristics. The actual selection of the content package may occur in an external device, such as a content category selector. Once the content package is selected, the apparatus may provide for output of the content package such as through displaying the content package on a display.

Abstract: An apparatus for enabling provision of context access with property or interface obfuscation may include at least one processor and at least one memory including computer program code. The at least one memory and the computer program code may be configured, with the processor, to cause the apparatus to perform at least receiving, from an application, a request for access to property information corresponding to a provider node in which the access is provided via a delivery context client interface based context model, determining access rights associated with the application based on a classification of the application, enabling masking of a portion of information associated with the access rights in response to the classification of the application defining a corresponding subclass restriction, and enabling access to the property via the context model based on the access rights associated with the application and subject to the masking. A corresponding method and computer program product are also provided.

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: Techniques to provide context-indexed network resources include determining a network resource that is associated with first data in response to receiving first data that describes a context feature. A context token is determined, which indicates a probability, in the first data, of a topic from a context vocabulary. The context vocabulary includes concepts describing temporal, spatial, environmental or activity circumstances of consumers. Second data is stored, which indicates the network resource in association with the context token. In some embodiments, determining a network resource associated with the first data includes sending a topic based on the feature context token to a network resource search engine; and, the network resource is determined based on data returned from the network resource search engine.

Abstract: An approach is presented for providing data providers for recommendations services. A data provider platform receives at least one request for at least one recommendation from at least one device. The data provider platform further determines context information associated with the at least one device, a user of the at least one device, or a combination thereof. The data provider platform further processes and/or facilitates a processing of the context information to determine, at least in part, one or more providers for generating the at least one recommendation.

Abstract: An approach is provided for providing recommendations within context-based boundaries. A recommendation platform receives an input, from a device, for selecting at least one content recommendation channel, wherein the at least one content recommendation channel includes, at least in part, one or more context-based boundaries for selecting one or more content items. Next, the recommendation platform determines context information associated with the device, a user of the device, or a combination thereof. Then, the recommendation platform processes and/or facilitates a processing of the context information based, at least in part, on the at least one content recommendation channel to cause, at least in part, a selection of the one or more content items.

Abstract: An approach is provided for providing rule-based recommendations. The approach involves a processing of one or more user profile tags, context tags, content tags, channel tags and/or other context information. The approach further involves a determination of one or more weighting factors of one or more of the user profile tags, context tags, content tags, channel tags and other context information. The approach also involves an application of one or more rule sets that bases a determination of a recommendation on the weighting factor. The approach, then, generates one or more recommendations.

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 presented for providing recommendation channels. A recommendation platform receives an input for creating at least one recommendation channel, the input specifying at least one category. Next, the recommendation platform determines one or more tokens based, at least in part, on the at least one category, wherein at least one of the one or more tokens represents context information. Then, the recommendation platform determines to create the at least one recommendation channel based, at least in part, on the one or more tokens.

Abstract: An approach is provided for providing recommendations based on a recommendation model and a context-based rule. A recommendation platform receives a request for generating at least one recommendation, the request including at least one user identifier, at least one application identifier, or a combination thereof. Next, the recommendation platform determines at least one recommendation model associated with the at least one user identifier, the at least one application identifier, or a combination thereof. Then, the recommendation platform determines at least one context-based recommendation rule. Then, the recommendation platform processes and/or facilitates a processing of the at least one recommendation model, the at least one context-based recommendation rule, or a combination thereof for generating the at least one recommendation.

Abstract: An approach is provided for providing recommendations based on a recommendation model and a context-based rule. A recommendation platform receives a request for generating at least one recommendation, the request including at least one user identifier, at least one application identifier, or a combination thereof. Next, the recommendation platform determines at least one recommendation model associated with the at least one user identifier, the at least one application identifier, or a combination thereof. Then, the recommendation platform determines at least one context-based recommendation rule. Then, the recommendation platform processes and/or facilitates a processing of the at least one recommendation model, the at least one context-based recommendation rule, or a combination thereof for generating the at least one recommendation.

Abstract: An approach is provided for providing recommendations based on a recommendation model and a context-based rule. A recommendation platform receives a request for generating at least one recommendation, the request including at least one user identifier, at least one application identifier, or a combination thereof. Next, the recommendation platform determines at least one recommendation model associated with the at least one user identifier, the at least one application identifier, or a combination thereof. Then, the recommendation platform determines at least one context-based recommendation rule. Then, the recommendation platform processes and/or facilitates a processing of the at least one recommendation model, the at least one context-based recommendation rule, or a combination thereof for generating the at least one recommendation.

Abstract: An approach is provided for providing rule-based recommendations. A recommendation platform determines one or more contexts for at least one level of a hierarchy of one or more context parameters. The hierarchy reflects different granularities of the one or more context parameters. The recommendation platform determines to generate at least one rule set based, at least in part, on the one or more contexts and then determines to include the at least one rule set in the hierarchy for generating recommendation information for one or more applications.

Abstract: An apparatus may include a monitoring module configured to monitor user interactions by a user with applications. A contextual characteristics determiner may determine one or more contextual characteristics relating to the user interactions, and the contextual characteristics may be categorized based on an ontology model. Thereby, a data model builder may build a user behavior model for the user based at least in part on the user interactions and the contextual characteristics. The apparatus may provide for private storage of the user behavior module. A recommendation module may issue a recommendation, which may be mapped to one of the applications, based at least in part on the user behavior model. The recommendation may be issued in response to a query from a query module. The query may include current contextual characteristics of the user and/or the apparatus.

Abstract: An apparatus may include a content package selector configured to provide for selection of a content package including one or more selectable segments. A monitoring module may be configured to insert a script into the content package. Further, the monitoring module may monitor one or more user interactions with the selectable segments as directed by the script. The apparatus may further determine one or more contextual characteristics relating to the user interactions. Thereby, the user interactions, the contextual characteristics, and/or the selectable segments may be stored and/or transmitted so as to build a data model based thereon. The data model may be used to make content recommendations based on the monitored user interactions and determined contextual characteristics as they related to the user interaction events with the selectable segments of the content package.

Abstract: An apparatus may include a content channel drafting module configured to provide for drafting of a content channel. A content channel comparison module may compare the content channel with existing content channels to determine a similarity factor. A channel creation determination module may determine whether or not to allow creation of the content channel based at least in part on the similarity factor. Thereby, creation of the content channel may be allowed in instances in which the similarity factor is less than a threshold correlation value and disallowed in instances in which the similarity factor exceeds the threshold correlation value. Further, when creation of a content channel is allowed, selection of a public channel status configured to allow sharing of the content channel may be disallowed in an instance in which the similarity factor exceeds a lower threshold correlation value.

Abstract: An approach is provided for providing a framework for generating recommendation models. A recommendation engine receives a request, at the recommendation engine, for generating a recommendation model for an application, wherein the recommendation engine is applicable to a plurality of applications. Next, the recommendation engine determines to retrieve rating information from on one or more profiles associated with the application, one or more other applications, or a combination thereof. Then, the recommendation engine determines to generate the recommendation model based, at least in part, on the rating information.

Abstract: An approach is provided for modeling relations among data items of an information resource. A modeling manager retrieves, at a device, a first data item and determines one or more data types associated with the first data item. Based, at least in part, on the one or more data types, the modeling manager determines one or more relations corresponding to the first data item based, at least in part, on the one or more data types. The modeling manager then associates the first data item with a second data item based, at least in part, on a semantic relationship among the first data item, the second data item, the one or more relations, or a combination thereof.

Abstract: Techniques for identifying network functions include determining first data that indicates a concept represented in content provided by a device. A function provided by a network service is determined based on the first data. In some embodiments, techniques include forming a data structure that associates each function of a plurality of functions provided by a plurality of network services with at least one identifier for a concept.