A computer-implemented method includes determining whether historical profile data structures are stored in a database with corresponding structured supplemental data and selected health care plan option identifiers of a set of health care plan option identifiers. The method includes generating historical feature vectors using the historical data structures stored in the database or generating the historical feature vectors using created sample profile data structures. The method includes training machine learning models using the generated historical feature vectors, selecting one of the machine learning models for use in generating recommendation outputs, presenting an interactive voice interface to an entity to generate audio questions and prompts for obtaining response data from the entity, classifying voice survey responses of the entity, and generating feature vectors. The method includes processing, using the selected machine learning model, the feature vectors to generate the recommendation outputs, and transforming a user interface to display the recommendation output.

A method is disclosed. A data set including: (a) identifiers of a set of incidents occurring within a defined geographic region to which at least one service provider responded during a first time period and (b) address data identifying a location within the geographic region of each said incident of the set is retrieved over a network. An instruction to generate a heat map of the incidents occurring within the geographic region during the first time period is received from a user via a user interface generated to a display device. In response to the instruction to generate the heat map, the address data is converted to GPS data. A heat map of an aerial view of the geographic region based on the GPS data is generated. The heat map is displayed to the display device in a user interface.

Provided is a process of learning an audience member function, the process including: obtaining a training set of geographic data describing geolocation histories of a plurality of mobile devices, wherein members of the training set are classified according to whether the respective member of the training set is a member of an audience; retrieving attributes of geolocations in the geolocation histories from a geographic information system; learning feature functions of an audience member function based on the training set, wherein at least some of the feature functions are a function of the retrieved attributes of geolocation, wherein the feature functions are learned, at least in part, by calculating a plurality of impurity measures for candidate feature functions and selecting one of the candidate feature functions based on the relative values of the impurity measures; and storing the feature functions of the audience member function in an audience repository.

A recommendation server is provided. The recommendation server includes a communicator configured to receive, from a first device, when a first user's input for communicating with a second user is received by the first device of the first user, a transmission request with respect to a list of a plurality of items of content related to an operation of the first device which was performed when the first user and the second user met each other; and a controller configured to determine a time when the first user and the second user met each other, based on at least one of first user's activity information of the first user and second user's activity information of the second user, and to provide, to the first device, a list of a plurality of items of content related to an operation of the first device which was performed at the determined time.

Disclosed herein are systems and methods of individual level learning that include receiving purchase event data from a merchant device that indicates that a purchase event occurred by a user on a user device, and transmitting the purchase event data to an analytics server. The methods may also include processing the purchase event data. The processing may include calculating a time gap for each of two sequential purchase events in a list of purchase events, and calculating an average duration of consecutive events by averaging all of the purchase events in the list of purchase events. The method may determine a purchase hazard probability that a purchase event will occur on a given day, when the average duration of consecutive events is larger than a standard deviation of the event occurring. When the purchase hazard probability is above a threshold, the system may push a message to the user device.

A method, apparatus and computer program product are provided for generating recommendations of autonomous vehicles that satisfy a personalized autonomous transition tolerance. In context of a method, the method receives a route request associated with a user and determines a personalized vehicle recommendation of one or more autonomous vehicles for the user based upon historical data associated with the user regarding prior vehicle selections including historical data relating to an autonomous transition tolerance to changes in autonomy level of a vehicle during traversal of a route. The method also causes transmission of the personalized vehicle recommendation to a user device associated with the user.

Embodiments generally relate to tour operations and travel management. In some implementations, a method includes generating one or more tour forming components, where the one or more tour forming components include one or more of a transportation component, an accommodation component, a catering component, a supply component, a sightseeing component, an activities component, a services component, and an events component. The method further includes generating one or more itineraries for one or more travelers, where each itinerary of the one or more itineraries is based on at least the one or more tour forming components.

A virtual local presence display apparatus, system and method is disclosed. Included are an extraction engine capable of automatically disassociating the virtual local presence from its production background; a first data feed of an actual background in which the displaying device resides; a background data feed of a plurality of optional backgrounds including at least the production background of the virtual local presence; a stream subject data feed of an extracted one of the virtual local presence extracted from the production background; an integrated data feed in which the virtual local presence and a background are integrated; a first processing having a receiver capable of receiving the data feeds and assessing a plurality of focal lengths to focal planes for the virtual presence in the production background, and in a selected one of the other backgrounds; and a second processing for causing displaying, on the display device, the virtual presence at a suitable location with regard to the focal planes in a selected one of the other backgrounds.

Techniques described herein are directed to e-commerce tags in multimedia content. In an example, multimedia content is received and item-recognition techniques are performed to identify one or more items referenced in the content. An interactive element is generated that indicates information about a given referenced item, and that interactive element is displayed while the multimedia content is output. Selection of the interactive element may cause a purchasing user interface to be displayed with item and/or or payment information prepopulated based at least in part on identified attributes of the item and/or user preferences determined from historical purchase data associated with the user.

A method and a system that gives any brand or retailer instant visibility by crowd-servicing grocery shoppers using a photo based app and dashboard are disclosed. Instant visibility in 24 hours with no emails, calls and waiting for half the price on a monthly subscription, all delivered in a neat dashboard and created by grocery shoppers using the intuitive app technology.