Abstract: One or more computing devices, systems, and/or methods for content recommendations using historical future data are provided. A model serving delay time is computed as an average of training delays of events. A historical data time interval is determined based upon the model serving delay time. A model is trained for predicting user content preferences using historic user distribution data and historic content distribution data associated with the historic data time interval. The model is utilized to generate and provide content recommendations to users.

Abstract: Managing electronic addresses based on communication patterns. A method includes tracking metadata of a plurality of electronic communications of a user. One or more lists of electronic addresses of recipients are generated for the user based on the metadata. Electronic addresses of potential recipients are identified from the one or more lists in response to an input indicative of selection of an electronic address of a recipient. The identified electronic addresses are recommended to the user. An input indicative of one or more electronic addresses selected by the user from the identified electronic addresses is received. Further, an electronic message is sent to the selected electronic addresses.

Abstract: Systems and methods are disclosed for utilizing a comment moderation bot for detecting and normalizing neologisms in social media. One method comprises transmitting, by a neologism normalization system, a comment moderation bot for detecting neologisms on an online platform maintained by one or more publisher systems. The comment moderation bot may aggregate data related to user comments and transmit the aggregated data to the neologism normalization system for further processing. The neologism normalization system implements unsupervised machine learning models for detecting neologisms in the aggregated data through tokenization and filtering; and normalizing the neologisms through similarity analysis and lattice decoding.

Abstract: The present teaching relates to system, method, and programming for indexing user records. A plurality of user records are obtained, wherein each user record is associated with a user identifier and one or more data-segments. For each data-segment, one or more user identifiers associated with the data-segment are determined, a relative distance of each user identifier with respect to a previous user identifier associated with the data-segment is computed, and a variable number of bits to be used to store the relative distance of each user identifier in a bit stream are determined based on a criterion associated with the relative distance. Offset values are generated for the one or more data-segments, wherein an offset value of a data-segment indicates an index of the bit stream where information of a first user identifier associated with the data-segment is stored.

Abstract: A method is provided, including: storing comments generated in response to a content item served over a network; analyzing the comments to determine features associated with each of the comments; using a scoring model to score each comment based on the comment's corresponding features; receiving a request to serve a subset of the comments; responsive to the request, selecting a ranking of the comments that is one permutation from possible rankings of the comments, wherein selecting the ranking is in accordance with a probability distribution of the possible rankings that is based on the scores of the comments; serving comments identified by the selected ranking over the network to a client device; determining a dwell time on the served comments; applying the dwell time to update the scoring model.

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: 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: Disclosed are systems and methods 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 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 allowing web browsing in a user interface of an electronic messaging system. The disclosed systems and methods automatically display electronic messages containing item information displayed in an electronic message in place of any web page links associated with the item enabling browsing of the item information from within the electronic messaging system's user interface.

Abstract: One or more computing devices, systems, and/or methods for searching across multiple user interfaces are provided. For example, a search query may be received from a user of a computing environment. A set of user interfaces, hosted by the computing environment, may be identified (e.g., mobile apps of a mobile operating system, browser tabs of a web browser, etc.). Content within the set of user interfaces may be queried using the search query to identify search results of the search query (e.g., webpages, social network posts, emails, or other content matching the search query). In an example, cached content of the user interfaces (e.g., recently accessed emails cached within a local content buffer cache by the web browser) may be searched using the search query for efficient querying of relevant content, such as through local or offline querying. The search results may be provided to the user.

Abstract: Disclosed is a system and method for email management that leverages information derived from automatically generated messages in order to identify types of messages and message content. The disclosed systems and methods apply the information learned from decoding previously received messages to other messages in a user's inbox to fully, or at least partially decode the information included within such messages. The disclosed systems and methods analyze messages received in a user's inbox to detect message specific information corresponding to types of content in the message and the location of such content in the messages. The message specific information is then applied to other newly received or identified messages to learn message specific information about those messages. Based on such learning, information can be extracted from such messages in order to increase a user's experience and increase monetization.

Abstract: Methods and apparatus for using features of images representing content items to improve the presentation of the content items are disclosed. In one embodiment, a plurality of digital images are obtained, where each of the images represents a corresponding one of a plurality of content items Image features of each of the digital images are determined. Additional features including at least one of user features pertaining to a user of a client device or contextual features pertaining to the client device are ascertained. At least a portion of the content items are provided via a network to the client device using features that include or are derived from both the image features of each of the plurality of digital images and the additional features.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for providing users with electronic retrieval capabilities that are activated upon the users' determined locations respective to real-world locations associated with a message providing entity. The disclosed technology combines the previously separate systems of mail extraction, geo-fencing and content delivery (e.g., notification) into a single system that efficiently manages a user's inbox in order to provide the user with content the user has expressly indicated is of interest to that user.

Abstract: At least one label prediction model is trained, or learned, using training data that may comprise training instances that may be missing one or more labels. The at least one label prediction model may be used in identifying a content item's ground-truth label set comprising an indicator for each label in the label set indicating whether or not the label is applicable to the content item.

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: The present teaching relates to providing a query suggestion. In one example, a request is received for query suggestions with respect to a query prefix input by a user. A plurality of query suggestions is determined based on the query prefix and a preceding query input by the user. A degree of popularity of the preceding query is determined. One or more query suggestions are selected from the plurality of query suggestions based on the degree of popularity of the preceding query. The one or more query suggestions are provided as a response to the request.

Abstract: One or more computing devices, systems, and/or methods for hyper parameter optimization for machine learning ensemble generation are provided. For example, one or more base models are trained using diverse sets of hyper parameters, wherein different sets of hyper parameters (e.g., hyper parameters with different values) are used to train different base models. A matrix, populated with predictions from the set of base models, is generated. A machine learning ensemble is generated by processing the matrix utilizing a meta learner.

Abstract: One or more computing devices, systems, and/or methods for selecting messages for transmission to client devices are provided. A first message associated with a first entity may be received from a first client device. The first message may comprise information associated with the first entity. A user account database, comprising a plurality of user profiles, may be analyzed based upon the first message to select a set of user accounts, from a plurality of user accounts, for transmission of a set of messages associated with the first message. The plurality of user accounts may be subscribed to an information service. Each user profile of the plurality of user profiles may comprise information corresponding to a user account of the plurality of user account. The set of messages may be transmitted to the set of user accounts.

Abstract: The present teaching relates to a method, system, and programming for providing content. A plurality of content items and publication information related thereto are obtained. For each of the plurality of content items, one or more topics are determined in accordance with a model. The related publication information associated with each content item is analyzed to identify at least one source of a plurality of sources that published the content item. A distribution is generated of each of the plurality of content items with respect to the plurality of sources and the one or more topics of the content item, and a bias of a source with respect to publishing content is identified based on the distributions of the plurality of content items.

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: Software for online active learning receives content posted to an online stream at a website. The software converts the content into an elemental representation and inputs the elemental representation into a probit model to obtain a predictive probability that the content is abusive. The software also calculates an importance weight based on the elemental representation. And the software updates the probit model using the content, the importance weight, and an acquired label if a condition is met. The condition depends on an instrumental distribution. The software removes the content from the online stream if a condition is met. The condition depends on the predictive probability, if an acquired label is unavailable.