Abstract: Disclosed herein is a statistical approach, a win share approach, used to assign a win share value to content items. User interaction with content items is tracked, and a win share value is assigned to content items in response to a “winning” action performed by a user. Win shares associated with content items are used to identify content items that are to be presented, and can further be used to identify an optimal presentation, e.g., layout, presentation frequency, etc., of content items that is to be presented.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in a content system supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data across platforms, which data 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 a breaking news story and track breaking developments in such story. The present disclosure can construct a breaking news storyline from the developments in the detected breaking news story, whereby a user can view the storyline as individual breaking news messages or as a complete timeline of events displayed on a provided page.

Abstract: In an example, sets of event information associated with events may be identified. The events may include intentional click events, accidental click events and/or skip events. Accidental click probabilities associated with the accidental click events and/or the skip events may be determined. Machine learning model training may be performed, using the sets of event information associated with the events and labels associated with the events, to generate a first machine learning model. The labels may include second labels associated with the intentional click events and/or third labels associated with the accidental click events and/or the skip events. The second labels may correspond to an intentional click classification. The third labels may be based upon the accidental click probabilities. Click probabilities associated with content items may be determined using the first machine learning model. A content item may be selected for presentation via a client device based upon the click probabilities.

Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.

Abstract: One or more computing devices, systems, and/or methods for generating time-preserving embeddings are provided. User trails of user activities performed by users are generated. Frequencies at which the activities were performed are identified. Indices are assigned to a set of activities identified from the activities as having frequencies above a threshold. Activity descriptions of the set of activities are mapped to the indices to generate a vocabulary. A model is trained using the user trails, timestamps of the activities, and the vocabulary to learn a set of time-preserving embeddings.

Abstract: A content delivery system for generating personalized content for a user. The system maintains an interest graph that shows the user's current attachment to one or more topics. When a user performs an action, a topic is determined for the action and the user's interest graph is modified based on the action. The system also receives content and analyzes the language of the content to determine a topic of the content. A similarity between the user's interests and the content is determined. The content is also analyzed to determine the popularity of the content. The user's interest level and the popularity of the content are then used to provide the user with a personalized content, such as a content recommendation or enhanced content.

Abstract: The present teaching relates to analyzing user behavior associated with web contents. Information related to user interactions associated with a content item placed on a reference property is first obtained. A measurement associated with each user interaction of the content item is determined based on the obtained information. An analyzing model for the content item which characterizes statistics of the measurements associated with the content item is further constructed. A measurement threshold to be used to determine a cost of placing the content item on a target property is further determined using the constructed analyzing model.

Abstract: In general, the present disclosure includes a system, method and architecture for use in analyzing content of a social network data to identify a financial market trend, e.g., a trend associated with a financial market instrument.

Abstract: One or more computing devices, systems, and/or methods for facilitating communications with service providers using disposable email addresses (DEAs) are provided. A first email, associated with a requested service, may be received from an email account. A set of service providers may be determined based upon the requested service. A DEA corresponding to the email account may be generated. A second email, comprising an indication of the DEA, may be generated based upon the first email. The second email may be transmitted to a set of email accounts associated with the set of service providers. Emails received from the set of email accounts that are addressed to the DEA may be transmitted to the email account. Responsive to receiving a request to deactivate the DEA from a device associated with the email account and/or responsive to determining that the requested service is completed, the DEA may be deactivated.

Abstract: One or more computing devices, systems, and/or methods for mailbox-based coupon display are provided. For example, a plurality of email messages stored in a mailbox of a first email account of a first user may be identified, and may be evaluated to identify a plurality of coupons. The plurality of coupons may be analyzed to determine one or more coupon features. User data and/or activity data associated with the first user may be analyzed to determine one or more user features. A predictive model may be tuned based upon the one or more coupon features and/or the one or more user features. A set of scores may be generated for the plurality of coupons based upon the predictive model. A graphical user interface may be controlled based upon the set of scores to display one or more coupons.

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 iterative process may be performed to identify a coalition network associated with fraudulent activity. The iterative process may include analyzing the first network profile to identify a first set of entities, of the first entities, that are related to an entity of the second entities, and/or analyzing the first network profile to identify a second set of entities, of the second entities, that are related to the first set of entities. Multiple iterations may be performed to identify the coalition network.

Abstract: A method for presenting personalized content to a user includes receiving user data corresponding to a user having a user profile, the user data including at least one or more messages in a user mailbox and a user web browser history within a network, extracting one or more data tags from the received user data, associated at least one data tag with a message, finding information in the network that corresponds to the associated data tag, generating a notification for the user, the notification including the found information in the network, and outputting the generated notification to a user interface of a device of the user.

Abstract: One or more computing devices, systems, and/or methods for video encoding are provided. For example, a video file may be segmented into at least a first portion and a second portion. The first portion may be analyzed to determine that the first portion is associated with a first level of complexity, and the second portion may be analyzed to determine that the second portion is associated with a second level of complexity. A first bitrate associated with the first level of complexity may be determined, and a second bitrate associated with the second level of complexity may be determined. The first portion may be encoded at the first bitrate to generate a first encoded portion, and the second portion may be encoded at the second bitrate to generate a second encoded portion. The first encoded portion and the second encoded portion may be assembled to generate an optimized video file.

Abstract: In an example, a companion user account is generated without a user specifying a username of the companion user account, wherein the companion user account is different than a primary user account of the user. A first interface, that provides access to resources associated with the primary user account, is displayed via a client application. A second interface, that provides access to resources associated with the companion user account, is displayed via the client application. A content targeting profile associated with the companion user account is generated based upon activity associated with the companion user account and/or one or more interests selected by the user. A subset of content items is selected, from among a plurality of content items and based upon the content targeting profile, for presentation via the second interface associated with the companion user account. A content item of the subset of content items is displayed via the second interface.

Abstract: Disclosed are systems and methods for automatically deleting messages from a recipient's inbox. The disclosed systems and methods provide the ability for automatic actions to be taken on delivered messages based on a passage of time. This enables a sender of messages, email service provider and/or email platform to exert control over sent messages to limit the number and type of operations that may be performed on such messages. For example, operations such as saving, forwarding, printing, copying, or otherwise duplicating the message and/or message data can be prohibited and all together rendered impossible. The disclosed systems and methods enables the purging of messages and associated message data from a recipient's inbox at a certain specified time, after the passage of a pre-determined amount of time, or upon the detection of a specified event.

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 framework for delivering electronic messages to a recipient in an optimized manner based on current real-world and digital activities associated with the recipient. Once a message sent by a sender is received by the message platform, the message and information related to a user's activity is analyzed, and a delivery condition is determined by the messaging platform. The platform then sends the message according to that delivery condition, such that it is delivered to the user only upon the platform relaying the message thereon when the condition is satisfied or occurs.

Abstract: The present teaching relates to a method, system, and programming for encrypted searching. In a search session, a uniform resource locator (URL) is received, wherein a portion of the URL is encrypted via a first key. A second key associated with the first key is obtained. A determination is made regarding whether a time-related criterion associated with the second key is satisfied. In response to the time-related criterion being satisfied, the portion of the URL is decrypted based on the second key to obtain a keyword, one or more search results are obtained based on the keyword, and a webpage including the one or more search results to be provided to a user is generated.

Abstract: One or more computing devices, systems, and/or methods for controlling an output device are provided. For example, features are extracted from data points of an object. A set of data points are identified from the data points based upon the set of data points having features corresponding to target features. Marker elements are assigned to the set of data points. A mapping structure is used to assign output indicators to the marker elements. The output device is controlled to provide output indicators assigned to marker elements as the marker elements become a current focus of the user navigation.

Abstract: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising receiving an event that includes a plurality of fields and extracting needed fields from the plurality of fields. The method then serializes the plurality of fields and generates a new event that includes the set of needed fields and a hidden field, the value of the hidden field comprising the serialized fields. The method then transmits the new event for processing using at least one processing stage of a stream processor. In response, the method reserializes a processed event generated by the stream processor and outputs the reserialized event to a downstream consumer.

Abstract: The present teaching, which includes methods, systems and computer-readable media, relates to providing query suggestions based on a number of data sources including person's personal data and non-personal data. The disclosed techniques may include receiving an input from a person, obtaining a first set of suggestions based on information from a first data source, presenting the first set of suggestions to the person, and presenting, to the person, a second set of suggestions obtained from a person corpus when a portion of the person corpus relevant to the input is accessible. The person corpus may be from a second data source that is private to the person.