Abstract: One or more computing devices, systems, and/or methods for generating a user-specific interface are provided. In an example, a user-specific machine learning model, for a user of an email application, may be trained based upon one or more interactions of the user with a device upon which the email application is installed. A determination may be made that an email message has been received by an email account of the user. A user-specific message interface may be generated based upon (i) the trained user-specific machine learning model and (ii) content of the email message. A notification of the email message may be provided for display on the device of the user. In response to the user selecting the notification of the email message, the user-specific interface may be provided for display on the device of the user.

Abstract: The present teaching relates to method and system for advertising. The method obtains information related to an operational smart attribution evaluation package (SAEP) posted on a platform. The SAEP is related to a conversion associated with an advertisement displayed by a plurality of entities. The method parses the SAEP to obtain a conversion parameter, and generates a claim for the conversion based on the conversion parameter and information related to the advertisement, if the advertisement was previously displayed. Further, the method transmits the generated claim to the SAEP to be evaluated whether a reward is to be allocated.

Abstract: The present teaching relates to a fraud detecting system and method for providing protection against fraudulent advertisement requests. Upon receiving a request for an advertisement, the system extracts an identifier, associated with a source from which the request originates, included in the request. The system determines whether the extracted identifier is included in a list of designated identifiers, and when the identifier is included in the list, the system denies the request for the advertisement. When the identifier is not included in the list of designated identifiers, the system provides the advertisement in response to the request, and extracts a set of features from the request and other requests that originate from the source to determine whether the identifier associated with the source is to be included in the list of designated identifiers based on the set of features in accordance with one or more models.

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 for a model training framework are provided. A definition and configuration of a model are received. Computations that the model will perform during training of the model are setup based upon the definition and configuration. Summary statistics to be tracked during training are specified. A batch of training data is input into the model to train the model based upon hyper parameters specified in the configuration of the model, and the summary statistics are tacked during the training. The parameters of the model are updated based upon a function corresponding to accuracy of the model processing the training data. The summary statistics are outputted.

Abstract: Disclosed are systems and methods utilizing neural contextual bandit for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to make item recommendations using latent relations and latent representations, which can improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods use neural network modeling in automatic selection of a number of items for recommendation to a user and using feedback in connection with the recommendation for further training of the model(s).

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: A system, apparatus, and method are presented for allocating for allocating advertisements for display are provided that include collecting a plurality of advertising spaces, each advertising space having at least one associated advertising space variable; collecting a media inventory, the media inventory comprising a plurality of advertisements, each advertisement having at least one associated advertisement variable; receiving a bid price and a target inventory percentage for each advertisement: receiving a request for an advertisement to be placed at a specified advertising space; identifying advertisements in the media inventory that are qualified to receive an impression at the specified advertising space; creating a qualified advertisement ranking by sorting the qualified advertisements by bid price; selecting advertisements from the qualified advertisement ranking until the sum of target inventory percentages of selected advertisements is equal to or greater than 100 percent; and allocating advertising

Abstract: The present teaching relates to obtaining a model for identifying content matching a query. Training data are received which include queries, advertisements, and hyperlinks. A plurality of subwords are identified from each of the queries and a plurality of vectors for the plurality of subwords of each of the queries are obtained. Via a neural network, a vector for each of the queries is derived based on a plurality of vectors for the plurality of subwords of the query. A query/ads model is obtained via optimization with respect to an objective function, based on vectors associated with the plurality of subwords of each of the queries and vectors for the queries obtained from the neural network.

Abstract: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising processing a plurality of events using a stream processor and executing a deduplication process on the plurality of events using the stream processor. The plurality of events is outputted to a streaming queue and a close of books (COB) of a data transport is detected. Then, an audit process is initiated in response to detecting the COB signal, the audit process comprising comparing a set of raw events to a set of events in the streaming queue to identify a set of missing events, and replaying a set of missing events through the stream processor.

Abstract: The present teaching relates to method, system, medium, and implementations for identifying k nearest neighbors. One or more KNN lists corresponding to one or more source data points are received. Each KNN list includes K neighbors of a source data point and each of the K neighbors is a data point represented by an index. Neighbor pairs and reverse neighbor pairs are generated based on the one or more KNN lists. The neighbor pairs and reverse neighbor pairs having the same source data point are grouped to generate a grouped pairs of neighbors for the source data point. A local join operation is performed based on grouped pairs of neighbors for each source data point to generate a combined neighborhood for the source data point, which is then sent to a KNN server, where combined neighborhoods generated by multiple local join executors are integrated to update a plurality of global KNN lists.

Abstract: Method, system, and programs for measuring user engagement with content items. In one example, a query is received. A set of content items related to the query is obtained. A presentation of at least one content item of the set of content items is provided on a user interface. A user activity related to the at least one content item is determined. An amount of time between a time at which the presentation of the at least one content item is provided on the user interface and a time at which the user activity occurred is determined. A score associated with the content item is determined based on the amount of time. Information related to user engagement with the set of content items is generated based on the score.

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: The disclosed systems and methods provide a novel framework that parameterizes columns in a templated virtual semantic layer. The disclosed framework enables inter- and cross-column relationships between stored data within a SQL database to be determined and stored, and then leveraged at query time to enable an optimized search of the data within the database. The disclosed framework enables a database to be construed, modified and/or configured according to a hierarchy, and/or with types of metadata, that corresponds to the determined column relationships. This not only reduces the amount of data stored and reduces the time to process queries, but also enables a more streamlined approach for searches to be constructed and executed, which can increase the performance of the database and the operations of systems that are backed by the database.

Abstract: The disclosed systems and methods provide a novel framework that provides mechanisms for performing cost-effective, accurate and scalable detection and recognition of fine-grained events. The framework functions by training high precision and high recall object/optical character recognition (OCR) models and aligning video frames to text commentaries of the videos (e.g., licensed play-by-play). The disclosed framework operates as a single algorithm that performs multimodal alignments between events/actions within videos and their prescribed text. Thus, the disclosed framework is able to scale to fine-grained action categories across different venues by delving into the key frames and key aspects of a video to identify particular actions performed by particular actors, thereby providing the novelty of fine-granted action detection and recognition.

Abstract: The present teaching relates to a method, system, and programming for searching content. A sketch of an object is obtained from a user. The sketch is processed by a neural network to generate an image corresponding to the sketch of the object. One or more features are extracted from the image, and one or more images previously stored are identified that have features similar to the one or more features. The one or more images are provided to the user.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content communicating, displaying, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods determine and display message content within a portion of a message inbox in a manner that is specific to the type message content. According to some embodiments, when a message is received in a message inbox of a user, the message content can be opened for display within a dedicated portion of the inbox, thereby enabling improved message content retrieval, access and navigation within a message platform or message application.

Abstract: In an example, a first set of text may be received from a client device. A set of content items may be selected from among content items based upon the first set of text and a plurality of sets of content item text associated with the content items. A set of terms may be determined based upon the first set of text and the set of content items. A similarity profile associated with the set of terms may be generated. The similarity profile is indicative of similarity scores associated with similarities between terms of the set of terms. Relevance scores associated with the set of terms may be determined based upon the similarity profile. One or more search terms may be selected from among the set of terms based upon the relevance scores. A search may be performed based upon the one or more search terms.

Abstract: Disclosed are systems and methods for generating recommendations to users based on historical travel information and electronic communication data. The disclosed systems and methods provide a novel framework for automating the transmission of electronic travel-related recommendations to users by consistently monitoring electronic messages received at an electronic communication mailbox corresponding to a user. The disclosed framework operates by leveraging historical user data, data parsed from electronic communication mailbox corresponding to a user, or various vendor information, and using the aforementioned data as inputs for travel-related recommendation models, in order to generate and transmit the optimal travel-related recommendations to a user.

Abstract: Systems and methods are disclosed for traffic filtration by content providers. One method includes receiving a content request from a device of a user; determining whether one or more container tags are associated with requested content; determining, prior to responding to the content request, whether the content request is by a user based on the content request and the one or more container tags; generating, prior to responding to the content request, an ad request based on the content request and the one or more container tags; determining, prior to responding to the content request, an ad request recipient based on the generated ad request and the one or more container tags; transmitting the ad request to the determined ad request recipient; and transmitting, over the electronic network to the device, a response to the content request when the content request is determined to be by a user.