Abstract: An approach is provided for determining the context-aware similarity between applications. A similarity platform processes one or more context logs associated with one or more devices to determine one or more context intents. The similarity platform further determines one or more distributions of one or more applications executed at the one or more devices with respect to the one or more context intents. The similarity platform also determines a context-aware similarity between two or more applications based, at least in part, on the one or more application distributions.

Abstract: An approach is provided for optimally matching advertisements to content items for targeted consumers using the content distribution characteristics. A distribution processor determines one or more distribution characteristics of one or more first content items that are distributed among one or more devices. The distribution processor then processes and/or facilitates processing of the one or more distribution characteristics to cause, at least in part, a selection of one or more second content items. In one scenario, the one or more second content items may include advertisements. From there, the distribution processor processes and/or facilitates a processing of the one or more first content items to cause, at least in part, an embedding of the one or more second content items in the one or more first content items.

Abstract: An approach is provided for characterizing user behavior patterns. The behavior pattern platform receives a plurality of context records from a device. Next, the behavior pattern platform places one or more contexts from the context records. Then, the behavior pattern platform places the contexts into one or more context groups. Then, the behavior pattern platform receives interaction data from the device, associates the context groups with the interaction data, and determines a behavior pattern based, at least in part, on the association of the context groups and the interaction data.

Abstract: An approach is provided for providing hub-based indexing and services. The hub-based platform causes, at least in part, an indexing of location-based content according to one or more location hubs of one or more transportation lines, Next, the hub-based platform determines a current proximity, a predicted proximity, or a combination thereof of one or more devices to the one or more location hubs, wherein the one or more devices are (a) traveling on the one or more transportation lines, (b) predicted to travel on the one or more transportation lines, or (c) a combination thereof. Then, the hub-based platform causes, at least in part, a presentation of at least a portion of the location-based content based, at least in part, on the current proximity, the predicted proximity, or a combination thereof.

Abstract: An approach is provided for determining a predicted duration of a context. A context duration platform causes, at least in part, a determination, a prediction, or a combination thereof of one or more contexts associated with at least one device. The context duration platform further processes and/or facilitates a processing of context information associated with the at least one device, other context information associated with one or more other devices, or a combination thereof to determine one or more predicted durations of the one or more contexts.

Abstract: An approach is provided for determining significant places with greatly improved accuracy using universally available identifier information. A significant place platform causes, at least in part, a mapping of one or more communication coverage areas associated with one or more identifiers onto at least one geo-grid, wherein the one or more identifiers are associated with at least one device operating within at least one communication network. The significant place platform further processes the one or more identifiers to determine one or more significance scores associated with one or more grid units of the at least one geo-grid. The significant place platform also determines at least one significant place based, at least in part, on the one or more significance scores.

Abstract: An approach is provided for providing group context sensing and inference. The group context platform determines at least one group of one or more devices that have one or more group contexts that are at least substantially similar, at least substantially correlated, or a combination thereof. Next, the group context platform causes, at least in part, a distribution of one or more context sensing tasks among the one or more devices of the at least one group. Then, the group context platform processes and/or facilitates a processing of one or more results of the one or more context sensing tasks to (a) modify the one or more group contexts; (b) enhance the one or more group contexts; (c) determine one or more other group contexts; or (d) a combination thereof.

Abstract: A context-aware adaptive authentication method may comprise: determining a context for a user; adjusting automatically an authentication configuration for the user based at least in part on the context, wherein different matching accuracies of an authentication algorithm for the same authentication input data are associated with respective authentication configurations; and performing an authentication of the user with the authentication configuration, wherein for the user under a safe context, the authentication is performed by decreasing a matching accuracy of the authentication algorithm.

Abstract: Example approach is provided for surveys. An example method may include monitoring a location of a user equipment of a public land mobile network to determine when the monitored location corresponds to a survey trigger corresponding to a survey served by a server; sending to the server a request for content of the survey, when the monitored location corresponds to the survey trigger; and receiving, in response to the request, the content of the survey selected in accordance with a context derived from at least the monitored location. Furthermore, the location may include the user's general situation as a survey trigger condition to enable survey selection.

Abstract: An approach is provided for providing an optimization framework for task-oriented event execution. A planner platform processes and/or facilitates a processing of user indication information to determine an event associated with a device, a user of the device, or a combination thereof. The planner platform further causes, at least in part, a creation of a planner object specifying, at least in part, one or more processes related to the event, one or more triggers for the one or more processes, or a combination thereof. The planner platform also causes, at least in part, an execution of the one or more processes at the device, one or more other devices, or a combination thereof based, at least in part, on a monitoring of contextual information against the one or more triggers.

Abstract: The exemplary embodiments of the invention provide at least a method, apparatus and system to perform operations including receiving context data from an electronic device, causing, at least in part based on the received context data, an identification of at least one context model compatible with the electronic device, and causing, at least in part, provision of the electronic device with the at least one compatible context model. In addition, the exemplary embodiments of the invention further provide at least a method, apparatus and system to perform operations including causing, at least in part, a provision of context data associated with an electronic device to a context inference service, in response, receiving a context model from the context inference service, and causing adaptation of the received context model as a current context model of the electronic device.

Abstract: A method for personalized location privacy recommendation comprises: obtaining information of one or more locations for a user; collecting features of the one or more locations; and recommending respective privacy levels of the one or more locations automatically based at least in part on the information and the features.

Abstract: An apparatus for providing text independent voice conversion may include a first voice conversion model and a second voice conversion model. The first voice conversion model may be trained with respect to conversion of training source speech to synthetic speech corresponding to the training source speech. The second voice conversion model may be trained with respect to conversion to training target speech from synthetic speech corresponding to the training target speech. An output of the first voice conversion model may be communicated to the second voice conversion model to process source speech input into the first voice conversion model into target speech corresponding to the source speech as the output of the second voice conversion model.

Abstract: An approach is provided for generating one or more recommendations to a user based on interactions the user may have with items or topics of interest. The approach involves processing and/or facilitating a processing of one or more interactions of a user with one or more content items. The approach further involves causing, at least in part, an accumulation of the one or more processed interactions of the user. The approach also involves causing, at least in part, a determination of one or more user preferences based, at least in part, on the accumulated one or more processed interactions. The approach additionally involves causing, at least in part, a generation of a rating score of the user for the topic based, at least in part, on the one or more user preferences.

Abstract: An approach is provided for feature-based collaborative filtering. A recommendation engine receives a request to generate one or more recommendations with respect to one or more items for one or more users. The recommendation engine processes and/or facilitates a processing of descriptive information associated with the one or more items to generate a mapping of the one or more items to one or more features. In one embodiment, the mapping brings performance improvements particularly when applied to time-dependent and/or keyword-based items. The recommendation engine then determines preference information with respect to the one or more features for the one or more users. Based, at least in part, on the mapping and the preference information, the recommendation engine generates the one or more recommendations.

Abstract: An apparatus for providing text independent voice conversion may include a first voice conversion model and a second voice conversion model. The first voice conversion model may be trained with respect to conversion of training source speech to synthetic speech corresponding to the training source speech. The second voice conversion model may be trained with respect to conversion to training target speech from synthetic speech corresponding to the training target speech. An output of the first voice conversion model may be communicated to the second voice conversion model to process source speech input into the first voice conversion model into target speech corresponding to the source speech as the output of the second voice conversion model.

Abstract: An approach is provided for providing recommendations to a user based on user's role derived from the context information and an advanced user profile. A recommendation platform processes context information to determine one or more roles associated with a user. Next, the recommendation platform calculates at least one level of similarity between the one or more roles and one or more other roles associated with one or more other users. Then, the recommendation platform determines recommendation information associated with the one or more other users based, at least in part, on the at least one level of similarity. Next, the recommendation platform processes the recommendation information to generate one or more recommendations for the user.

Abstract: An apparatus for determining one more preferred words of a user may include a processor and memory storing executable computer program code that cause the apparatus to at least perform operations including implementing a topic model including data associated with one or more word preferences of at least one user. The computer program code may further cause the apparatus to implement a training model of the topic model to generate the word preferences based in part on analyzing training data of the training model. The training data including content associated with one or more determined topics. The computer program code may further cause the apparatus to determine that the word preferences correspond to one or more preferred words of respective users. Corresponding methods and computer program products are also provided.

Abstract: An approach is provided for a holistic framework to model user item rating with user generated tag information. A tagging manager determines one or more tags associated with one or more items, wherein the one or more tags are generated by one or more users. The tagging manager processes and/or facilitates a processing of the one or more tags to cause, at least in part, a generation of one or more semantic spaces. The one or more semantic spaces and/or one or more semantic concepts within the one or more semantic spaces represent one or more groupings of the one or more tags. The tagging manager determines one or more probability parameters that the one or more tags, the one or more users, the one or more items, or a combination thereof are associated with respective ones of the one or more semantic concepts in the semantic spaces.

Abstract: An approach is provided for diversifying recommendation results. A diversification manager determines one or more recommendation scores associated with one or more items. The one or more recommendation scores are for determining a sort order of the one or more items. The diversification manager then determines similarity information associated with the one or more items, and processes and/or facilitates a processing of the similarity information to cause, at least in part, an adjustment of the one or more recommendation scores, the sort order, or a combination thereof.