Abstract: Improved systems and methods for enhancing the performance of network based computerized content rendering and hosting and providing of devices, systems and/or platforms by modifying the capabilities and providing non-native functionality to such devices, systems and/or platforms through a novel and improved application, networked based enforcement of geographical compliance, data processing and networking framework.

Abstract: In some aspects, the techniques described herein relate to a method including: obtaining, by a computing device, a set of messages, each message including message metadata and message structure, at least one message of the set of messages comprising a digital asset; clustering, by the computing device, the set of messages based on the message metadata and the message structure; classifying, by the computing device, the clusters into categories; determining, by the computing device, a digital asset structure from at least one message cluster; and generating, by the computing device, at least one mapping rule based on the digital asset structure.

Abstract: Technologies for selectively streaming video based on mapping buffer data to download rates. The technologies can include sampling download rates of a video player prior to or during downloading of a first video segment to the video player. The technologies can include determining a range of download rates of the video player based at least on the sampled download rates. The technologies can include determining an amount of accumulated video data in a buffer of the video player immediately prior to or during the downloading of the first video segment. Also, the technologies can include mapping the determined amount of accumulated video data to a download rate within the determined range of download rates using a mapping function, and determining a second video segment quality for a second video segment based at least on the mapped download rate.

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: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel recommendation framework that automatically applies transfer learning from a knowledge-base and generating a multi-variable based unified recommendation. The framework dynamically develops a universal word dictionary between a source language and a target language based on Natural Language Processing (NLP word embeddings. This not only leverages the accuracy of multi-lingual product embeddings, but also increases the efficiency and effectiveness in how it can be applied. The disclosed systems and methods, therefore, provides a novel computerized solution for how different knowledges learnt from one electronic platform can be adapted to a global platform for providing global users electronic information.

Abstract: The disclosed systems and methods provide a novel framework that provides mechanisms for a Deep & Cross Network (DCN) framework that performs distilled deep prediction for personalized stream ranking on portal websites. The disclosed framework is scalable to satisfy the much more stringent latency and computational requirements required by current network operating environments. The disclosed framework is able to dynamically evaluate and leverage live traffic on network sites in order to provide, update and maintain current recommendations for users as they traverse to a portal and when they navigate within the portal. The disclosed framework implements a DCN model(s) that is capable of being compressed into a model size for a unified optimization within a live traffic environment by combining knowledge distillation and model compression techniques. The disclosed framework is built as a light-weight deep learning model that can be served in production and perform on par with large models.

Abstract: Systems and methods are provided for improving web-based document retrieval and object manipulation. In an implementation, objects within web documents (e.g., a web page) are manipulated when the objects are visible through a viewport of a user's web browser. According to a method, an object selected from a web document is manipulated when that selected object is displayed within the viewport of the user's browser. The manipulation may include downloading content associated with the stored object and additionally, or alternatively, executing a script associated with the stored object. Additionally, or independently, methods may be provided for blocking the download of an object in a retrieved web document until that object is displayed or visible in the user's browser viewport.

Abstract: Techniques for automatic intelligent information extraction from an electronic document are disclosed. In one embodiment, a computerized method is disclosed comprising training a label prediction model to generate a set of label predictions, obtaining an electronic document, analyzing the electronic document and determining a set of features for each of a set of information items identified in the electronic document, obtaining model output from the label prediction model for each information item, the model output comprising, for a respective information item, a set of probabilities corresponding to a set of information classes, and generating an information extraction comprising a set of labels corresponding to the set of information items.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content 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 provide systems and methods for automatically creating a caption comprising a sequence of words in connection with digital content.

Abstract: A determination device according to the present application has an acquisition unit and a determination unit. The acquisition unit acquires the search queries, which are the search queries input by a plurality of input customers who have input the reference query and input within a predetermined period. The determination unit determines whether a predetermined period is appropriate or not based on the attributes of the input customers who have input search queries or based on whether these search queries satisfy predetermined conditions or not.

Abstract: The disclosed systems and methods provide a novel framework that enables cost-effective, accurate and scalable detection and recognition of key events in sporting or live events. The framework functions by creating a domain-specific video dataset with frame level annotations (i.e., deep domain datasets) and then training a lightweight camera view classifier to detect camera views for a given video. The disclosed framework uses pre-trained pose estimation and panoptic segmentation models along with geometric rules as labeling functions to define scene types and derive frame level classification training data. According to some embodiments, disclosed frameworks may be used to identify key persons or events, select a thumbnail corresponding to a key person or event, generate personalized highlights to enhance user experience and social media promotions for a team, sport or players, and predict and select the best camera view sequence for automatic highlights generation.

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: The present teaching relates to dynamically generating a card. In one example, a request is received for generating a card to be provided to a user. Dynamic information related to the request is obtained. One or more modules are selected to be put into the card based on the dynamic information. The card is generated based on the selected one or more modules.

Abstract: One or more computing devices, systems, and/or methods are provided. A request for content associated with a device and/or a set of request information associated with the request for content may be received. A content item may be transmitted to the device. A set of client information associated with the device may be received. The set of client information may be analyzed to determine a fraudulence label associated with the request for content. Fraud detection information generated based upon the set of request information, the set of client information and/or the fraudulence label may be stored in a fraud detection database. A second request for content associated with a second device and/or a second set of request information associated with the second request for content may be received. A second fraudulence label may be determined based upon the second set of request information and/or the fraud detection database.

Abstract: The present teaching relates to tracking an event at a plurality of distributed servers. In one example, an event to be tracked is determined. A user associated with the event is identified. A script is generated to be embedded in a web page. The script triggers an event message when the user performs an online behavior related to the web page in accordance with the event. The event message triggered by the script is received. A tracing flag is determined from the event message. An instruction is provided to the plurality of distributed servers for executing one or more applications based on the event and the tracing flag.

Abstract: A multimedia content item is summarized based on its audio track and a desired compression budget. The audio track is extracted and processed by an automatic speech recognizer to obtain a time-aligned text transcript. The text-transcript is partitioned into a plurality of segment sequences. An informativeness score based on a salience score and a diversity score is computed for each of the segments. A coherence score is also computed for the segments in the plurality of sequences. A subsequence of one of the segment sequences that optimizes for informativeness and coherence is selected for generating a new content item summarizing the multimedia content item.

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: 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: The disclosed embodiments are directed toward local emotion detection during live streaming events. A client device receives a video stream from a remote server and captures media content while displaying the video stream. The client device uses a local machine learning/artificial intelligence event detection model to detect events in the media content. The client device then transmits detected events to the remote server involved in the live stream. The client device may additionally stream the locally captured media content to the remote server. In response, the remote server provides an interaction dashboard and, in some embodiments, mixes the local media content with the live stream.

Abstract: Disclosed are methods and devices for converting mobile notifications to content using a local content exchange. In one embodiment, the method comprises receiving a request for content from a mobile application; querying a data store of available content, the data store of available content populated with one or more notifications received by other mobile applications installed on the mobile device; identifying a responsive notification for the request for content based on the querying, the content item identified based on bid parameters associated with the one or more notifications; and transmitting the responsive notification to the mobile application.