Abstract: Communication accounts may contain information such as account holder names, contact lists, and communication logs. Such information may be processed for generating features that may be used as corpus for a machine learning algorithm for developing classifiers of names. Specifically, names and contact names of the accounts may be arranged in to a document according to the manner in which account holders communicate with the contacts. The document may be used for generating word embedding of the names. Names prelabeled with ethnicity together with their word embedding may be used as training data for developing ethnicity classifiers based on machine learning algorithms.

Abstract: The present teaching relates to generating user profiles with semantic knowledge. A first information associated with a user is obtained. One or more entities are identified from the first information. The one or more entities are augmented based on second information to generate a set of augmented entities. The set of augmented entities are clustered into a set of hierarchical clusters. A set of user profiles is generated based on the set of hierarchical clusters so that the user profile is to be used to personalize content recommendation.

Abstract: A method that incorporates teachings of the subject disclosure may include, for example performing, by a wireless communication device comprising a processor, wireless telephony communications via a first wireless interface, transmitting information associated with media-related activities to a server, receiving from the server a media recommendation that is generated according to the information associated with media-related activities, initiating communications with a network via a second wireless interface, downloading a media content item of the media recommendation from a content provider via the second wireless interface, and presenting the media content item at a display. Other embodiments are disclosed.

Abstract: Systems and methods for managing advertisement campaign are provided. The system includes one or more devices having a processor and a non-transitory storage medium accessible to the hardware processor. The system includes a memory storing a database including campaign data. The system also includes a server computer in communication with the database. The server computer is programmed to receive a budget to be spent on a plurality of websites. The server computer is programmed to estimate a parameter for a non-linear model based on the campaign data. The server computer is programmed to estimate an expected number of conversions for each of the plurality of websites using the non-linear model with the estimated parameter. The server computer is programmed to determine an allocation of impressions for the plurality of websites that maximizes an estimated total number of conversions.

Abstract: A method that incorporates teachings of the subject disclosure may include, for example performing, by a wireless communication device comprising a processor, wireless telephony communications via a first wireless interface, transmitting information associated with media-related activities to a server, receiving from the server a media recommendation that is generated according to the information associated with media-related activities, initiating communications with a network via a second wireless interface, downloading a media content item of the media recommendation from a content provider via the second wireless interface, and presenting the media content item at a display. Other embodiments are disclosed.

Abstract: A method that incorporates teachings of the subject disclosure may include, for example performing, by a wireless communication device comprising a processor, wireless telephony communications via a first wireless interface, transmitting information associated with media-related activities to a server, receiving from the server a media recommendation that is generated according to the information associated with media-related activities, initiating communications with a network via a second wireless interface, downloading a media content item of the media recommendation from a content provider via the second wireless interface, and presenting the media content item at a display. Other embodiments are disclosed.

Abstract: Relational data can be visualized in a map representation. A plurality of vertices and edges are determined based on a set of data identifying objects (i.e., vertices) and relationships (i.e., edges). The vertices and edges are embedded in a planar graph and a Voronoi diagram is generated based at least the plurality of vertices within a set of bounding-points located at least a distance away from the vertices of the map. A bounding-box is associated with each of the vertices, and a set of points generated along each bounding-box. The Voronoi diagram is generated based on the vertices and the set of points of each bounding-box. Each resulting Voronoi cell associated with a common vertex is merged to form a plurality of common cells (i.e., map). The size of each bounding-box can correlate to the importance of its associated vertex, and the points along the bounding-box can be randomly perturbed.

Abstract: Methods, systems, and products are disclosed for graphing data. A layout is retrieved that comprises locations for vertices. A proximity graph is generated using triangulation. Nodal overlaps are removed.

Abstract: Systems and methods to provide a recommendation engine that uses implicit feedback observations are provided. A particular method includes receiving accessing data comprising a plurality of implicit feedback observations for a plurality of users. The plurality of users includes a first user that requested a recommendation. Each implicit feedback observation is associated with a particular user and a particular item of a plurality of items. The method includes determining a plurality of preference ratings and a plurality of confidence ratings for each user of the plurality of users for each item based on the plurality of implicit feedback observations. The method includes generating a recommendation list of one or more of the plurality of items for the first user based on the plurality of preference ratings and the plurality of confidence ratings.

Abstract: Relational data can be visualized in a map representation. A plurality of vertices and edges are determined based on a set of data identifying objects (i.e., vertices) and relationships (i.e., edges). The vertices and edges are embedded in a planar graph and a Voronoi diagram is generated based at least the plurality of vertices within a set of bounding-points located at least a distance away from the vertices of the map. A bounding-box is associated with each of the vertices, and a set of points generated along each bounding-box. The Voronoi diagram is generated based on the vertices and the set of points of each bounding-box. Each resulting Voronoi cell associated with a common vertex is merged to form a plurality of common cells (i.e., map). The size of each bounding-box can correlate to the importance of its associated vertex, and the points along the bounding-box can be randomly perturbed.

Abstract: Methods, systems, and products are disclosed for graphing data. A layout is retrieved that comprises locations for vertices. A proximity graph is generated using triangulation. Nodal overlaps are removed.

Abstract: Methods, systems, and products are disclosed for graphing data. A layout is retrieved that comprises locations for vertices. A proximity location is generated for each vertex. Each vertex's location from the layout is merged with each vertex's proximity location. A cost function associated with the layout is minimized.