Abstract: The present teaching relates to automatic formality classification and transformation of online text items. In one example, a request is received for determining a formality level of a text item in an online communication. One or more linguistic features are extracted from the text item. Contextual information with respect to the online communication is extracted. A formality level of the text item is determined based on the one or more linguistic features and the contextual information. The formality level represents a degree of formality of the text item. The formality level is provided as a response to the request.

Abstract: Disclosed are embodiments for replacing database table join keys with index keys. In one embodiment, a method is disclosed comprising: receiving, by a processor, annotation data, the annotation data comprising a set of rows; retrieving, by the processor, a root dataset, the root dataset stored in one or more files; generating, by the processor, a row identifier for each row in the set of rows, the row identifier storing a plurality of fields enabling alignment of a respective row in the annotation data to a corresponding row in the root dataset; generating, by the processor, an annotation dataset, the annotation dataset comprising the set of rows and corresponding row identifiers; and writing, by the processor, the annotation dataset to at least one file, the at least one file separate from the one or more files.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in electronic messaging, and other, 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 generating data extraction rules, which can then be used to automatically extract data from electronic messages.

Abstract: One or more computing devices, systems, and/or methods are provided. Event information associated with a plurality of events may be identified. The plurality of events may be associated with first entities corresponding to a first entity type and second entities associated with a second entity type. A first network profile associated with the first entities and the second entities may be generated based upon the event information. An arrangement of particles corresponding to the first entities and the second entities may be generated. Charges associated with the particles may be determined based upon the first network profile. The particles may be rearranged to a second arrangement of particles based upon the charges. One or more clusters of particles in the second arrangement of particles may be identified. One or more coalition networks associated with fraudulent activity may be identified based upon the one or more clusters of particles.

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: 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: 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 data processing and networking framework.

Abstract: The disclosed embodiments describe methods, devices, systems, and computer-readable media for synchronizing streamlining multimedia files among client devices. In the various embodiments, multiple client devices are configured to adjust playback of live multimedia content to synchronize playback in combination with a video conference.

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: Disclosed embodiments are methods, apparatuses, and computer-readable media for annotating distributed data without redundant data copying. In one embodiment, a method is disclosed comprising reading a raw dataset, the raw dataset comprising a first set of columns and a first set of rows; generating an annotation dataset, the annotation dataset comprising a second set of columns and a second set of rows; assigning row identifiers to each row in the second set of rows, the row identifiers aligning the second set of rows with the first set of rows based on the underlying storage of the raw dataset and annotation dataset; and writing the annotation dataset to a distributed storage medium.

Abstract: Briefly, embodiments of methods and/or systems of generating preference indices for contiguous portions of digital images are disclosed. For one embodiment, as an example, parameters of a neural network may be developed to generate object labels for digital images. The developed parameters may be transferred to a neural network utilized to generate signal sample value levels corresponding to preference indices for contiguous portions of digital images.

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: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising receiving an event, such as a streaming event, from a client. The method determines that the event comprises a primary event and, if so, writes the primary event to a cache and returning the primary event to the client. The method later receives a second event from the client, the second event associated with the first event, annotates the second event based on the primary event, and returns the annotated second event to the client.

Abstract: Event logs in a video advertisement insertion network are processed to remove duplicate entries. One or more ad servers are continuously generating new event entries and writing them to a database. The entries are randomized such that generated time contiguous entries are distributed over multiple storage locations, thereby facilitating resource scaling and a uniform use of storage and computing resources. The distributed entries are read from the storage locations using sequential reads of chunks of the entries and processed to remove duplicate entries.

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: 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: One or more computing devices, systems, and/or methods for future event recommendation are provided. For example, messages of a user account of a user are parsed to identify messages corresponding to events attended by the user. Event features are extracted from the messages, where an event feature is descriptive of an aspect of an event. An event database of future events is queried using the event features to identify future events having one or more of the event features. A description of the future events is constructed and provided to the user.

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: 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: 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: 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.

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 framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video ad experience for viewing users. The disclosed framework operates by leveraging available surfaces in videos to show advertisements in compliance with publisher protection, compliance and policy in a fully automatic, end-to-end solution. 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 content in compliance with the digital rights of the owners of the content being merged via the disclosed augmentation.

Abstract: One or more computing devices, systems, and/or methods are provided. Activity of a plurality of devices may be analyzed to identify network traffic. A network profile associated with the plurality of devices may be generated based upon the network traffic. The network profile may be indicative of one or more sets of transmission metrics associated with a first device of the plurality of devices. The network profile may be indicative of one or more sets of reception metrics associated with the first device. Content may be generated based upon the network profile. The content may be transmitted to a device based upon the network profile.

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: 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: 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: Systems and methods are disclosed for executing the electronic distribution of electronic content to a dynamic display.

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: Methods and apparatus for delivering content to an audience member via one or more mediums based on an audience member profile are disclosed. Profile data for audience members may be initially collected from an offline source, such as a registration or subscription database. The profile data may be stored in a dedicated database. The initial profile data may be supplemented periodically with data reflecting online activity by the audience member. The combined offline and online profile data may be used to group the audience members into segments. Audience member segments may be used to identify audience members who are targeted to receive like content. An audience member's inclusion in a segment may be indicated by storing a segment-targeting cookie on the audience member computer. Content may be delivered to the audience member based on identification of the segment in the segment-targeting cookie.

Abstract: An information processing device according to the present application includes an acquisition unit, a selection unit, and a search unit. The acquisition unit acquires a search query input by a user. The selection unit selects a type of target information to be searched on the basis of the search query acquired by the acquisition unit. The search unit searches for information corresponding to the search query from the type of target information to be searched selected by the selection unit.

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: Systems and methods are disclosed for providing non-intrusive advertising content to users. The method includes receiving user input reflecting user content preferences for receiving desired content related to specific topics in lieu of standard advertising slots while watching playable media content via a set-top box. The method may further include receiving a request for playable media content and then retrieving desired content based on user content preferences. Thereafter, the method may include choosing non-intrusive advertising content and generating datagrams that include the desired content and the non-intrusive advertising content. The datagrams may be concatenated with the playable media content to generate displayable content. The display content may then be provided for displaying.

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: According to one aspect of an embodiment a learning apparatus includes a first acquiring unit that acquires first output information that is output by an output layer when predetermined input information is input to a model that includes an input layer, a plurality of intermediate layers, and the output layer. The learning apparatus includes a second acquiring unit that acquires intermediate output information that is based on pieces of intermediate information that are output by the plurality of intermediate layers when the input information is input to the model. The learning apparatus includes a learning unit that learns the model based on the first output information and the intermediate output information.

Abstract: An information processing apparatus according to the present application includes an acquiring unit and a deciding unit. The acquiring unit acquires attribute information on a user. The deciding unit decides, based on the attribute information acquired by the acquiring unit, a placement position in which a virtual riding point that corresponds to a riding point that is used for the user to ride in a moving vehicle and that is virtually set is placed.

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: 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.

Abstract: In one embodiment, a user of a client device may selectively share personal data with web companies. The personal data may be shared directly via transmission by the client device to the web companies. Alternatively, the personal data may be shared with the web companies via a personal data sharing system that collects and maintains personal data associated with users. The personal data sharing system may reward the user for sharing their personal data with the web companies.

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: The present disclosure generally relates to processing and organizing electronic content. In accordance with one implementation, a computer-implemented method is provided that comprises receiving source data from at least one content server, the source data being associated with electronic content. The method also includes generating local data based on at least one of an analysis of the received source data or an extraction from the received source data. Additionally, the method includes classifying the electronic content as being associated with one or more content stacks. Further, the method includes generating representations of the electronic content based on the local data and generating instructions to display at least one content stack on a user interface, each displayed contact stack being operable to display one or more of the representations of the electronic content associated with the content stack based on the classification.

Abstract: One or more computing devices, systems, and/or methods for generating and providing recommendations of products are provided. For example, content is extracted from a message sent to a user. The content is evaluated to identify a product identifier corresponding to a product title of a product. If the product identifier is a truncated version of the product title, then a database of product titles and frequencies of occurrence of the product titles is used to complete the product title. A model is used to infer a product category for the product title. Matching scores are assigned to products within a product category based upon weighted attributes. A recommendation is provided to the user for a product having a matching score greater than a matching threshold.