Abstract: An analytics module included in a processing system receives performance feedback related to a broadcast media item. The performance feedback includes metadata associated with the feedback. Based on the metadata, the analytics module distinguishes between first performance feedback provided by automated programs and second performance feedback provided by valid users. The second performance feedback is transmitted to a media proposal server, but the first performance feedback is not. The media proposal server determines, based on the second performance feedback, that the broadcast media item is to be replaced by a replacement broadcast media item.

Abstract: Systems and methods are provided in the field of online advertising and malicious software. In some embodiments, an apparatus for determining a degree of deceptiveness associated with a session presenting at least one online advertisement includes means for capturing electronic interactions among at least two entities involved in the session, the captured interactions including interaction-related properties and time, means for processing to filter a plurality of attributes for the one or more relations from the captured electronic interactions, each attribute defining a data type and corresponding data value, wherein the extraction is performed by integration with the two or more entities, apply one or more models to each of the one or more relations, and determine a degree of deceptiveness for each of the one or more relations based on the one or more applied models.

Abstract: Systems, methods, and computer-readable media are disclosed for estimating impressions for a digital out of home (DOOH) advertising spaces (e.g., digital billboards and screens). A DOOH advertising system may determine the location of relevant DOOH advertising spaces and the location of certain consumers with known attributes and a known location. Based on this information the DOOH advertising system may estimate a number of impressions for a given DOOH advertising space and a given consumer segment associated with attributes of consumers within a certain distance from the DOOH advertising space. Using this information, the DOOH advertising spaces having the highest estimated impressions for a given consumer segment may be identified.

Abstract: Embodiments of the present invention provide methods, systems, apparatuses, and computer program products for predicting consumer behavior. In one embodiment a method is provided comprising automatically creating a link graph comprising nodes representing webpages, links representing hyperlinks, and weights for each link representing a number of times a hyperlink associated with the respective link redirected the a user devices from a webpage associated with a first node connected to the link to a webpage associated with a second node connected to the link; and determining based on the link graph a programmatically expected path for a particular user, wherein the programmatically expected path identifies, at least, two or more webpages that the particular user is programmatically expected to visit and specifying a programmatically expected order at which the particular user will visit the webpages.

Abstract: A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data.

Abstract: A system and a method are disclosed for a platform that determines the classification of a physical asset received from a provider. For a physical asset, the platform extracts intrinsic data from the asset and compiles extrinsic data by web scraping data associated with the asset. The platform generates a principal component vector comprising the intrinsic data and extrinsic data and inputs the principal component vector into a machine learning model. The machine-learning model is trained using training data that includes an aggregation of principal components of a physical asset as labeled by a historical classification and a time associated with the entry. The machine-learning model outputs the classification of the physical asset corresponding to a present time. The platform provides the classification to a user in visual association with a representation of the physical asset.

Abstract: A device's location and an identifier corresponding to the device are received. The device's location is privatized by mapping it to landmarks proximate to the device's location, storing the proximate landmarks in association with the device's identifier, and discarding the received location data. The proximate landmarks are featurized to generate a model which is used to determine a value of the advertising opportunity corresponding to a target identifier.

Abstract: An information providing method includes the steps, executed by a computer capable of acquiring provision information, of acquiring identification information that is a trigger for acquiring the provision information, creating account data for accessing a mailbox that stores the provision information, on the basis of the identification information, acquiring the provision information stored in the mailbox by using the created account data and a predetermined code, and displaying the acquired provision information on a display part.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system using predictive models derived from tiered feature data.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media configured to use a per-set level optimization of the rank order of promotions to be recommended to a consumer. In some embodiments, machine learning is used offline to generate a predictive diversity model that receives one or more similarity rank features associated with a promotion (e.g., category, price band) as input, and produces an output multiplier to be applied to the promotion's respective associated relevance score (e.g., a relevance score representing a prediction of the promotion's conversion rate without diversity features). At run time, per-set optimization of the ordering of a set of promotions is implemented by adjusting the respective associated relevance scores of the promotions using the diversity model and then re-ordering the set of promotions based on their respective adjusted relevance scores.

Abstract: Methods, configured mobile devices, and computer-readable media for displaying content on mobile devices are disclosed. An exemplary of displaying content on a mobile device includes receiving a first content request provided by a native app executing on one or more processors of the mobile device; responsive to receiving the first content request, determining whether the native app is permitted to display app content on a lock screen of the mobile device, wherein said determining includes examining at least one of: mobile device location, mobile device motion, and date/time; and in the event that the native app is permitted to display app content on the lock screen of the mobile device: transmitting a second content request to a content server; receiving app content from the content server in response to the second content request; and displaying the app content on the lock screen of the mobile device.

Abstract: Systems and methods for audio advertising user interaction are disclosed. A voice interactive device causes an advertising audio file to be played for a user. The user can express interest in the advertising content of the advertising audio file by speaking one of a plurality of predetermined intents. Based on expressed user response, one or more results can be provided to the user and/or to a user device. The results relate to advertising content of the advertising audio file.

Abstract: An example apparatus disclosed herein includes a data input interface to access different sets of initial adjustment factors, the initial adjustment factors generated to correct at least one of misattribution or non-coverage of media impressions logged by a database proprietor, a grouping controller to identify a first set of the initial adjustment factors as a set of donor adjustment factors based on (a) first audience members associated with the set of donor adjustment factors satisfying a first threshold and (b) first impressions associated with the first audience members satisfying a second threshold, and identify a second set of the initial adjustment factors as a set of recipient adjustment factors, and an imputation factor generator to generate imputation factors to correct ones of the recipient adjustment factors based on ones of the donor adjustment factors.

Abstract: Embodiments of the present invention provide a computer system a computer program product, and a method that comprises, in response to receiving a request for a task to be performed, optimizing configured operational parameters based on prioritized user parameters and environmental details associated with the task; calculating a value of the task based, at least in part, the optimized configured parameters, environmental details associated with the task, and prioritized user parameters; and performing the task based on the optimized, configured parameters and calculated value.

Abstract: A control apparatus includes a controller configured to determine whether a user who travels in a vehicle has stopped off at a place different from a destination, with reference to positional data indicating a position of the user, the user having accepted a recommendation to stop off at the place using the vehicle, the recommendation being presented together with an advertisement promoting the place.

Abstract: An integrated system of a physical consumption environment and a network consumption environment and a control method thereof are provided. The control method of the integrated system of the physical consumption environment and the network consumption environment includes the following steps. A biological characteristic image of a consumer in the physical consumer environment is obtained. The biological characteristic image is identified to obtain an identity information from an identity database. An activity of the consumer in the physical consumption environment is detected. A product followed by the consumer and/or a physical behavior information are obtained according to the activity of the consumer in the physical consumption environment. A network behavior information of the consumer in the network consumer environment is obtained according to the identity information. A price of the product is dynamically adjusted according to the physical behavior information and the network behavior information.

Abstract: The device according to the present invention is configured to be able to communicate with a managing device managed by a retail company that sells a product, and the device comprises: delivery means for delivering an instruction that at least describes promotion work for promoting a sale of the product, to the managing device; reception means for receiving one or more evidences showing a result of the promotion work performed at the retail company according to the instruction, from the managing device; and calculation means for calculating a degree of achievement of the promotion work at the retail company based on the one or more evidences.

Abstract: Virtual teleportation systems and methods are disclosed. A remote advertising system includes an identification, location and authentication system associated with a physical venue, including a master sensor node and a plurality of sensors. A cloud-based advertisement service is deployed in the physical venue. An application installed on a mobile device determines a first set of coordinates corresponding to the mobile device location, transmits a first search request for a service, receives and displays a list of services, including the physical venue associated with the master sensor node and the physical venue including a teleportation indicator, and receives an indication that the teleportation indicator is selected. The application determines a second set of coordinates corresponding to the physical venue location, replaces the first set of coordinates with the second set of coordinates, transmits a second search request, and receives and displays a second list based on the second set of coordinates.

Abstract: The pull-type searching system provides an effective and efficient way to navigate deals and assist the user in identifying a deal for selection. The pull-type searching system further enables identification of one or more alternative deals to present to the user when no deals are identified for the selected search criteria. The pull-type searching system includes a method and apparatus. The method includes communicating ordered selectable search criteria, the search criteria including one or more categories, subcategories and deal types based on a user profile or available deals, or redemption goals. The method further includes receiving a selection from the search criteria and searching a deals database for results associated with the selection. Further, the method includes communicating the results associated with the selection, one or more alternative categories, or one or more alternative deals. A similar apparatus is provided.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers.