Abstract: Systems and methods are provided for determining a quantity of network location visitors that are likely generated or encouraged by specific offline events. A corresponding number of leads may then be attributed to and associated with those specific events. Ongoing conversion activity of those visitors may be tracked and associated with the offline events. Conversions of those visitors may be attributed entirely or partially to one or more specific offline events. The effectiveness of each offline may then be evaluated based on aggregate lead and conversion information.

Abstract: One or more computing devices, systems, and/or methods are provided. In an example, an internet resource identification item associated with one or more internet resources may be identified. User activity information associated with a plurality of events may be analyzed to determine a plurality of sets of text associated with the internet resource identification item, wherein each set of text of the plurality of sets of text is associated with an event, of the plurality of events, associated with an internet resource of the one or more internet resources. A plurality of term representations may be determined based upon the plurality of sets of text. A user intention-based representation associated with the internet resource identification item may be generated based upon the plurality of term representations. A content item may be selected for presentation via a client device based upon the user intention-based representation.

Abstract: A method of providing targeted content across user channels includes receiving a plurality of device activity events on a user device, storing the received plurality of device activity events, creating an audience population based on the stored device activity events, determining links for additional secondary user devices based on the user device, creating a cross-channel advertising campaign targeting the determined audience population, and running the cross-channel advertising campaign based on the device activity and the determined additional secondary user devices.

Abstract: Disclosed are systems and methods for rendering augmented videos on mobile devices and computing environment with limited computational resources. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video augmentation object experience for viewing users. The disclosed framework operates by leveraging available surfaces in digital content to show augmentation objects in compliance with various pre-established contextual and technical constraints. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the digital content based on the contextual and technical constraints, and the computational resources of the device augmented digital content is rendered on.

Abstract: Systems and methods are disclosed for associating a plurality of Internet-enabled devices with a common user profile for targeting Internet content or advertising. One method includes: receiving, from a plurality of Internet-enabled devices, a plurality of requests for electronic content or advertising; extracting, from each of the plurality of requests, a source IP address and a unique identifier associated with the respective Internet-enabled device; for each source IP address for which requests were received over a predetermined time period from a number of Internet-enabled devices below a threshold number of devices, identifying each possible pair of devices from which requests were received; and for each possible pair of devices, calculating a probability that the pair of devices are owned or operated by a common user.

Abstract: One or more computing devices, systems, and/or methods for isolated budget utilization are provided. A first budget pacing component is assigned to control bidding by a first content serving component for a set of content items. A second budget pacing component is assigned to control bidding by a second content serving component for the set of content items. The first budget pacing component controls the bidding by the first content serving component according to a first portion of a content item budget based upon a traffic share of the first content serving component. The second budget pacing component controls the bidding by the second content serving component according to a second portion of the content item budget based upon a traffic share of the second content serving component.

Abstract: Methods are disclosed for providing an ad-supported mobile data plan, where ad display may be tied to data usage levels and user input. A method includes receiving, using at least one processor, user interaction with advertisement content displayed on a device; retrieving, using the at least one processor, a data usage limit associated with the device; and causing a change in the data usage limit based on the user interaction with the advertisement content displayed on the device.

Abstract: Systems, apparatuses, and methods are provided for determining a bid value for placing an advertisement onto advertising space available through an electronic marketplace. A method is used for calculating the option value of maintaining the advertisement in the advertising space during one or more periods of time. The option value may be based on expected profits and the estimated future value of maintaining the advertisement. The option value may then be used to calculate the bid price for placing the advertisement.

Abstract: The present disclosure relates to systems and methods customizing electronic communications. A future event associated with a first user may be determined, and a second user that is associated with the first user may be identified. A plurality of communications involving the first user and the second user may be analyzed. A selection rule may be applied based on the analyzed plurality of communications, the selection rule identifying content from the database. Content from the database may be selected based on the application of the selection rule. An electronic message may be provided to the first user identifying the future event, and the selected content may be provided to the first user.

Abstract: Methods, systems, and computer-readable media are disclosed for utilizing unused network capacity for prefetch requests. One method includes: receiving, over a network, network traffic information from a network provider of the network; determining a threshold value for prefetch request fulfillment based on the received network traffic information; receiving, over the network, a plurality of prefetch requests from an application running on a mobile device connected to the network of the network provider; determining, for each prefetch request of the plurality of prefetch requests, a score for the prefetch request based on the received plurality of prefetch requests; and responding to, for each prefetch request of the plurality of prefetch requests, the prefetch request based on the determined threshold value and the determined score for the prefetch request.

Abstract: Systems and methods are disclosed for online distribution of content. One method includes: receiving, from a first content publisher, a request to publish, on a web page of a second content publisher in a network of publishers, a link to or preview of content of the first content publisher, wherein the request includes at least one parameter associated with at least one attribute of a desired viewer of the link to or preview of content; receiving, from the second content publisher in the network, a request for a link to or preview of content of a publisher in the network, the request including at least one identifier associated with a prospective viewer of a web page of the second content publisher; and determining whether to display a link to or preview of content of the first content publisher on the web page of the second content publisher.

Abstract: A method for online advertising, is provided, including: receiving a request for a web page from a client device; in response to the request, selecting an advertisement for presentation on the web page, and transmitting the web page to the client device; determining a duration of exposure of the advertisement when the web page is presented on the client device; determining a level of performance of a guaranteed presentation amount associated with the advertisement, the level of performance based on the duration of exposure of the advertisement. In another embodiment, a plurality of candidate advertisements are identified for presentation on a requested web page; for each candidate, an expected cost per time unit (eCPTU) of exposure is determined; one candidate advertisement is selected for presentation on the web page based on the eCPTU's; the web page is transmitted to a client device.

Abstract: Systems and methods are disclosed for processing electronic content, such as text, videos, and images. According to certain embodiments, user interactions with electronic content may be tracked over a plurality of modalities, such as web pages, email, mobile applications, and social media. The tracked user interactions may include copy/paste events, explicit user highlighting, social sharing, and user voting. Key passages of electronic content may be identified based on the tracked user interactions and ranked against one another. Ranking of passages may be based, for example, on a raw or normalized score for the identified key passages. Alternatively, the ranking of a passage may be based on a ratio of user interactions with the passage to total views of the electronic text containing the passage. One or more of the identified key passages (e.g., the highest ranked passages) may be published to one or more applications.

Abstract: Systems and methods are disclosed for determining segments of online users from a correlated dataset. One method includes receiving, over a network, a plurality of datasets including user-related data of a plurality of users, each dataset being transmitted from a data owner; correlating, by at least one processor, the plurality of datasets into a correlated dataset; receiving a segmentation request for determining a plurality of users that qualify for a segment, the segmentation request including a set of segment rules to apply to the correlated dataset; determining, by accessing the correlated dataset, whether each user of the plurality of users qualifies for the segment based on the segment rule; and storing an indication of the segment in the correlated dataset for each user determined to qualify for the segment.

Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.

Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.

Abstract: One or more computing devices, systems, and/or methods for generating dynamic content item recommendations are provided. Content item information, extracted from message data, is aggregated to calculate popularity and attributes of content items. The content items are ranked based upon the popularity and attributes to generate a ranked list of content items. Exploration traffic is served utilizing a set of eligible content items selected from the ranked list of content items. An eligible content item is promoted for participation in auctions for serving non-exploration traffic based upon the eligible content item being served a threshold number of times.

Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.

Abstract: Allocating bids for providing content within a segmented campaign is controlled to ensure that an event rate associated with the provided content meets or exceeds a threshold rate. A campaign-level event rate, associated with the provided content, is estimated and provided as a feedback signal. This feedback signal is employed to dynamically update bid allocations for each of the segments, which in turn varies the number or rate of provided impressions and events. Such feedback enables the control of the campaign-level rate and ensures that the campaign-level rate meets or exceeds the rate threshold. To control these rates, the number of total impressions, as well as the number of associated events, is temporally sampled across the campaign segments. Based on the number of impressions and events, the campaign-level event rate is estimated and employed as the feedback signal. Updating the bid allocations may be based on the Beta Distribution.

Abstract: The present teaching relates to a method and a system for advertising. The method obtains information about a conversion associated with an advertisement and generates with respect to the conversion, an operational smart attribution evaluation package (SAEP). The SAEP includes a conversion parameter and a reward. The method transmits the SAEP to a platform to be posted, and thereafter receives from the SAEP, an indication of an entity which is estimated to be associated with the conversion and to which the reward is to be allocated. The entity is determined by the SAEP based on the conversion parameter and information from a plurality of entities that displayed the advertisement.