Abstract: The disclosed systems and methods provide a cloud-based framework for the creation and/or enhancement of high quality media content for dissemination over a computerized network. The disclosed framework is configured to operate in accordance with at least one of a content creation, content enhancement and/or rendering template. Such templates can function as rules engines that call specific types of ML or AI algorithms or routines that modify the input data according to the type of template being used. Thus, the disclosed framework can be utilized for creating new high-quality media, improving upon existing media and/or reformatting media for rendering upon dissemination.

Abstract: Systems and methods are disclosed for identifying malicious traffic associated with a website.

Abstract: A novel framework optimizes SQL queries that are generated from a templated virtual sematic layer. The framework introduces the use of a virtual semantic layer into database management systems' operations, whereby templated SQL queries can be rewritten according to a determined and measured nesting, dimensional structure that produces an optimized search system. This enables templated SQL fragments to be translated for query optimization, thereby reducing the drain on a database's resources and minimizing a query's impact on the database's performance.

Abstract: One or more computing devices, systems, and/or methods for implementing a model for serving exploration traffic are provided. An amount of spend by a content provider to provide content items of the content provider through a content serving platform to client devices of users is determined. A number of exploration impressions of users viewing exploration content items of the content provider over a timespan is determined. A return on exploration impression metric is determined for the content provider based upon a ratio of the amount of spend to the number of exploration impressions. The return on exploration metric is used to rank available exploration content items of content providers for serving exploration traffic.

Abstract: One or more computing devices, systems, and/or methods for content cache invalidation using cache tags are provided. A first proxy hop may receive a request from a client device for a content object originating from a content source. A cache tagging script is executed to add a query parameter to the request to create a modified request. The query parameter specifies a cache tag version for the content object. The modified request is transmitted through one or more subsequent proxy hops to the content source to retrieve the content object. The content object, tagged with a cache tag specifying the cache tag version, is cached as a cached content object within a cache. The cache tag is associated with an expiration timestamp after which the cached content object is designated to be invalid.

Abstract: Disclosed herein is a statistical approach, a win share approach, used to assign a win share value to content items. User interaction with content items is tracked, and a win share value is assigned to content items in response to a “winning” action performed by a user. Win shares associated with content items are used to identify content items that are to be presented, and can further be used to identify an optimal presentation, e.g., layout, presentation frequency, etc., of content items that is to be presented.

Abstract: Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate and/or support one or more operations and/or techniques for machine learning (ML) classification of digital content for mobile communication devices, such as implemented in connection with one or more computing and/or communication networks and/or protocols.

Abstract: One or more computing devices, systems, and/or methods for determining whether requests for content are fraudulent are provided. A request for content may be received from a first device. A first user profile associated with the first device may be identified. The first user profile may comprise activity information associated with the first device, demographic information associated with the first device and/or interest information associated with the first device. A user profile database may be analyzed to identify a set of user profiles similar to the first user profile. A relevance score associated with the request for content may be generated based upon the resource, the set of user profiles and/or the first user profile. The relevance score may be compared with a threshold relevance to determine whether the request for content is fraudulent.

Abstract: In an example, sets of event information associated with events may be identified. The events may include intentional click events, accidental click events and/or skip events. Accidental click probabilities associated with the accidental click events and/or the skip events may be determined. Machine learning model training may be performed, using the sets of event information associated with the events and labels associated with the events, to generate a first machine learning model. The labels may include second labels associated with the intentional click events and/or third labels associated with the accidental click events and/or the skip events. The second labels may correspond to an intentional click classification. The third labels may be based upon the accidental click probabilities. Click probabilities associated with content items may be determined using the first machine learning model. A content item may be selected for presentation via a client device based upon the click probabilities.

Abstract: The present teaching relates to analyzing user behavior associated with web contents. Information related to user interactions associated with a content item placed on a reference property is first obtained. A measurement associated with each user interaction of the content item is determined based on the obtained information. An analyzing model for the content item which characterizes statistics of the measurements associated with the content item is further constructed. A measurement threshold to be used to determine a cost of placing the content item on a target property is further determined using the constructed analyzing model.

Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.

Abstract: One or more computing devices, systems, and/or methods for mailbox-based coupon display are provided. For example, a plurality of email messages stored in a mailbox of a first email account of a first user may be identified, and may be evaluated to identify a plurality of coupons. The plurality of coupons may be analyzed to determine one or more coupon features. User data and/or activity data associated with the first user may be analyzed to determine one or more user features. A predictive model may be tuned based upon the one or more coupon features and/or the one or more user features. A set of scores may be generated for the plurality of coupons based upon the predictive model. A graphical user interface may be controlled based upon the set of scores to display one or more coupons.

Abstract: In an example, a companion user account is generated without a user specifying a username of the companion user account, wherein the companion user account is different than a primary user account of the user. A first interface, that provides access to resources associated with the primary user account, is displayed via a client application. A second interface, that provides access to resources associated with the companion user account, is displayed via the client application. A content targeting profile associated with the companion user account is generated based upon activity associated with the companion user account and/or one or more interests selected by the user. A subset of content items is selected, from among a plurality of content items and based upon the content targeting profile, for presentation via the second interface associated with the companion user account. A content item of the subset of content items is displayed via the second interface.

Abstract: Systems and methods are disclosed for opting-out of targeted advertising in online advertising environments. One method includes receiving an opt-out verification request, the opt-out verification including an IP address of a user device and HTTP header fields of an HTTP request of the user device; determining a geographic area of the user device based on the IP address of the user device; accessing an opt-out database having entries of user devices that opted-out of receiving targeted advertising based on at least one HTTP header field of the HTTP request; determining whether the user device has opted-out of receiving targeted advertising based on the determined geographic area of the user device, the HTTP header fields of the HTTP quest, and the entries of user devices of the opt-out database; and transmitting a verification acknowledgement when the user device is determined to have opted-out of receiving targeted advertising.

Abstract: The present teaching relates to method, system, and programming for evaluating expressions. An expression indicative of conditions and metadata associated therewith is obtained. A determination is made as to whether the expression corresponds to a modified version of an earlier expression based on the metadata. In response to a determination that the expression is the modified version of the earlier expression, a query associated with the modified expression is transmitted to a forecasting cluster so that the modified expression is to be evaluated by the forecasting cluster. In response to a determination that the expression does not have a corresponding earlier expression, the expression is evaluated.

Abstract: Briefly, embodiments disclosed herein may relate to digital content selection, and more particularly to weighted pseudo-random digital content selection for use in and/or with online digital content delivery, such as online advertising, for example.

Abstract: In an example, an article may be analyzed to identify entity terms. Entity term relevance scores associated with the entity terms may be determined based upon the article and the entity terms. One or more first entity terms may be selected based upon the entity term relevance scores. One or more sets of reference position information associated with the one or more first entity terms may be determined. A first set of reference position information is based upon one or more positions, in the article, of one or more references to a first entity term. One or more second entity terms of the one or more first entity terms may be selected based upon the one or more sets of reference position information. A set of one or more salient entity tags associated with the article may be generated based upon the one or more second entity terms.

Abstract: Systems and methods are disclosed for sorting elements, such as bids in an auction environment or marketplace for the display of an advertisement on a web page. According to one implementation, a plurality of elements may be received over a network. For example, the plurality of elements may comprise a plurality of bids, each of which may include, for example, a bid price, a bid allocation, and a bid target. The received set of elements may be recursively partitioned into a plurality of element subsets. For example, the element set may be partitioned about a pivot selected from a sample set of elements chosen from the element set. A subset of elements may be identified from the element set as eligible elements (e.g., bids eligible for selection as a winning bid). Once the set of eligible elements has been identified, the recursive partitioning of elements may be terminated.

Abstract: A system for generating an advertisement is provided. The system may receive an advertisement request from a client device and select an advertisement from a database in response to the advertisement request. The system may identify an advertiser web server associated with the advertisement, for example a landing page. The system may retrieve a picture from the advertiser web server and integrate the picture with the advertisement to generate an enhanced advertisement. The system may serve the enhanced advertisement to the client device.

Abstract: One or more computing devices, systems, and/or methods are provided. A manifest associated with a first video may be generated. The manifest may include a first web address associated with accessing the first video, one or more first milestone markers of the first video, and/or one or more first beacon web addresses associated with the one or more first milestone markers. The manifest may be transmitted to a first client device. An indication addressed to a first beacon web address of the one or more first beacon web addresses may be received from the first client device. It may be determined, based upon the indication addressed to the first beacon web address, that the first client device displayed a first portion of the first video corresponding to a first milestone marker, of the one or more first milestone markers, associated with the first beacon web address.