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

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: 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: 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 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: 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: 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: 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: 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.