Computer software architectures are disclosed that use improved machine learning techniques for computer data security, data science, and data privacy protection. Computer operations are improved by more efficiently and effectively processing relevant data, such as web browsing history data. Web browsing data that are representative of web browsing history based on activity associated with a web browser application determined. Using a base model and based on the web browsing data, federated machine learning applied to past web browsing data representative of past web browsing history associated with other web browser applications other than the web browser application can be used to generate an updated targeted model.

A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Systems and methods for identifying and correlating an advertised object with a plurality of interconnected computing devices embedded in a living environment of the user. For example, a media guidance application implemented at a set-top box with a television may receive a signal from a printer indicating that cartridge ink is low. When the user is watching a television show and an advertisement relating to printer cartridges is being played, the media guidance application may identify that the advertised printer cartridges may be something that the user needs, and may then send a notification to a user of the advertisement. In this way, the media guidance application correlates advertisements from a media asset with a user's actual needs, which may improve the advertisement conversion rate for advertisers.

A device receives vehicle data associated with vehicles located at a vehicle dealership lot, and receives, from a user device, profile data identifying a user of the user device and data identifying a particular vehicle of the vehicles. The device compares the data identifying the particular vehicle and the vehicle data to determine particular vehicle data associated with the particular vehicle, and processes the particular vehicle data and the profile data of the user, with a first model, to determine purchase options for the particular vehicle and the user. The device provides, to the user device, the particular vehicle data and the purchase options for the particular vehicle to cause the user device to display the particular vehicle data and the purchase options for the particular vehicle.

Described is a system for learning and predicting key phrases. The system learns based on a dataset of historical forecasting questions, their associated time-series data for a quantity of interest, and associated keyword sets. The system learns the optimal policy of actions to take given the associated keyword sets and the optimal set of keywords which are predictive of the quantity of interest. Given a new forecasting question, the system extracts an initial keyword set from a new forecasting question, which are perturbed to generate an optimal predictive key-phrase set. Key-phrase time-series data are extracted for the optimal predictive key-phrase set, which are used to generate a forecast of future values for a value of interest. The forecast can be used for a variety of purposes, such as advertising online.

A system and method of displaying advertising content includes transmitting data associated with a vehicle to a data center. An advertisement is generated based on the transmitted data. The advertisement is transmitted to the vehicle. An evaluation period is determined during which the advertisement is prevented from being displayed. The advertisement is displayed on a display of an in-vehicle infotainment system following the evaluation period.

A method for interpreting messages, user-defined alert conditions, voice commands and performing an action in response is described. A method for annotating media content is described. A method for presenting additional content associated with media content identified based on a fingerprint is described. A method for identifying that an advertisement portion of media content is being played based on a fingerprint derived from the media content is described. A method of one media device recording particular media content automatically in response to another media device recording the particular media content is described. A method of concurrently playing media content on multiple devices is described. A method of publishing information associated with recording of media content is described. A method of deriving fingerprints by media devices that meet an idleness criteria is described. A method of loading, modifying, and displaying a high definition frame from a frame buffer is described. A method of recording or playing media content identified based on fingerprints is described.

A method for recommending household goods and clothing information to a first user of household goods and clothing, and an apparatus thereof. The method includes: transmitting a request for recommended household goods and clothing for the first user, to be displayed on the first user's display; receiving the purchase history of one or more of household goods and clothing by a plurality of users of the one or more of the household goods and clothing; extracting a second user, from among the plurality of users, who has purchased a household good or clothing with a design or function similar to a household good or clothing purchased by the first user; transmitting a recommendation for the first user of a household good or clothing purchased by the second user; and displaying on the display of the first user, the recommended household good or clothing purchased by the second user.

Systems and methods for optimizing base pricing of products within a physical retailer are provided. Such systems and methods include first collecting transaction logs for products in a set of physical retail spaces. These logs are validated, adjusted and elasticities between the products are computed. The adjustment may be responsive to the day, by retailer and by a host of external factors (e.g., weather). The adjustment may also include a normalization and filtering out of inaccurate log data. Elasticity is calculated by machine learning models. A set of constraints are then received and used, along with the elasticities to compute the optimal prices for deployment in retailers for further testing.

A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.