Abstract: A method includes executing operations to generate a first enhancement function based on a parent-child link in a content hierarchy including a link between a parent node in a first level of the content hierarchy to a child node in a second level of the content hierarchy below the first level. A second enhancement function is generated based on a sibling link in the content hierarchy including a link between a sibling node in a third level of the content hierarchy and a sibling node in the third level of the content hierarchy sharing a common parent node with the first sibling node in a fourth level of the content hierarchy above the third level. A user content consumption metric is generated based on the first and second enhancement functions. A content list including a set of candidate content items ranked based on the user content consumption metric is generated.

Abstract: The present teaching generally relates to detecting providing pre-validated data buckets for online experiments. In a non-limiting embodiment, user activity data representing user activity for a first plurality of user identifiers may be obtained. A first set of values and a second values, representing first and second user engagement parameters, respectively, may be generated for each user identifier based on the user activity data. A first ranking and a second ranking may be determined for the first and second sets, respectively. A first exclusion range including a first number of values to be removed from the first and second sets may be determined. A homogenous value set may be generated by removing the first number of values from the first and second sets, where each value from the homogenous value set corresponds to a user identifier available to be placed in a data bucket for an online experiment.

Abstract: One or more computing devices, systems, and/or methods for assessing riskiness of a domain are provided. For example, a content request is received from a content provider service that hosts a website associated with a domain. The content request is evaluated to identify request features. Feature scores are assigned to the request features using labeled feature data. The feature scores are aggregated to generate a content request risk score corresponding to a riskiness of the content request corresponding to fraud, such as domain spoofing. The content request risk score along with other content request risk scores of content requests associated with the content provider service are aggregated to create a content provider risk score corresponding to a riskiness of the content provider service, such as a risk of the domain being fraudulent. The content provider risk score is used to either block or process the content request.

Abstract: Method and system for group communication across electronic mail users and feature phone users. A method for receiving electronic mails on a feature phone includes receiving a text message on the feature phone in response to a first electronic mail. The method also includes calling a telephonic number embedded in the text message to listen to an audio clip of the first electronic mail and providing a voice input as a response to the first electronic mail. The system includes a feature phone that receives a plurality of electronic mails. The system also includes one or more electronic devices, and a communication interface in electronic communication with the feature phone and the one or more electronic devices. The system further includes a memory that stores instructions, and a processor responsive to the instructions to receive a text message in response to an electronic mail transmitted by an electronic mail user.

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: Systems and methods are provided for improved web searching. In one implementation, suggested search queries am provided based on previous search queries and click data. A weighted bi-partite graph or index may be used to identify related search queries based on overlapping clicked URLs. According to a method, query-click log data of a search engine is processed to generate sets of suggested search queries, data corresponding to each suggested search query, and a set of clicked URLs related to each suggested search query. Additionally, or independently, methods may be provided for contextually correcting spelling errors within sets of suggested search queries using a contextual algorithm, and/or identifying and discarding sets of suggested search queries and URLs that lead to restricted material, such as restricted content and related URLs.

Abstract: One or more computing devices, systems, and/or methods for controlling a graphical user interface using a presentation of messages based upon predicted interactions with the messages are provided. For example, a plurality of messages associated with the messaging account may be received. Interactions with the plurality of messages may be tracked to generate sets of message interactions. The plurality of messages may be analyzed to identify sets of attributes. An expected action model may be generated based upon the sets of message interactions and the sets of attributes. A set of messages associated with the messaging account may be analyzed based upon the expected action model to predict one or more interactions corresponding to one or more potential presentations of the set of messages. A presentation may be selected from the one or more potential presentations. A graphical user interface may be controlled using the presentation.

Abstract: One or more techniques and/or systems for sending push notifications of content items to client devices are provided herein. For example, an input received from a user can be expanded to obtain an expanded user interest. Content items from a content source can be filtered based upon the expanded user interest to obtain a set of filtered content items. A push notification can be constructed to comprise one or more of the filtered content items from the set of filtered content items. The push notification can be sent to a client device of the user for display as a device alert notification. In an example, the filtered content items, within the push notification, may be ranked based upon a ranking metric.

Abstract: Systems, devices, and methods for automating network account transfers based on predicted inactivity are disclosed.

Abstract: One or more computing devices, systems, and/or methods for providing a system with access to resources associated with a user account using a disposable email address (DEA) are provided. A request to provide a system with access to a first set of resources may be received. The first set of resources may be associated with a first email account associated with a first email address. A first DEA associated with the first email account may be generated. The first DEA may be transmitted to the system. A first set of modified emails may be generated based upon a first set of emails of the first email account. A first modified email of the first set of modified emails may comprise an indication of the first DEA. Access to the first set of modified emails may be provided to the system. The first DEA may be deactivated.

Abstract: Systems and methods are disclosed for determining if an account identifier is computer-generated. One method includes receiving the account identifier, dividing the account identifier into a plurality of fragments, and determining one or more features of at least one of the fragments. The method further includes determining the commonness of at least one of the fragments, and determining if the account identifier is computer-generated based on the features of at least one of the fragments, and the commonness of at least one of the fragments.

Abstract: Methods, systems, and computer programs are presented for displaying a customized news stream. One method includes an operation for identifying dwell times spent by users while accessing a first plurality of items, each item belonging to one media type from a plurality of media types (e.g., news articles, videos, slide shows, etc.). In addition, the method includes operations for determining statistical parameters for each media type based on the identified dwell times, and for detecting a news corpus having a second plurality of items. A priority for each item in the news corpus is determined based on the media type of the item, the corresponding statistical parameters for the media type of the item, and the profile of a user. The news stream is sent to the user for presentation on a display, the news stream being sorted based on the priority of the items in the news corpus.

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 messaging framework that automatically applies a multi-factor analysis technique to incoming and received messages in order to properly identify a message's type and category, which dictates the manner in which the message is displayed within a recipient's inbox. The disclosed framework operates on two levels: i) it determines whether a message is from a human or machine sender (H/M classification), and ii) it determines the messages category (MAGMA categorization).

Abstract: Disclosed are systems and methods for improving interactions with and between computers searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The methods and systems analyze digital message content in digital communication systems to automatically identify shared user interest(s), to automatically create computerized relationship matrix data identifying user connections, or relationships, using identified shared user interest(s), and to automatically provide a recommendation using the shared user interest and user relationships formed using the shared user interest.

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 a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction 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. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, 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 positive signal probabilities.

Abstract: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a system is disclosed comprising a stream processor configured to process events emitted by an event stream and output processed events; a queue configured to receive the processed events from the stream processor; a spooler configured to read the processed events from the queue and write the processed events to a buffer; and an auditor process configured to extract a written event from the buffer and confirm that the written event matches an event present in the event stream.

Abstract: Devices often receive content items to be saved for later presentation to a user. In some instances, the content of the message is analyzed to retrieve supplemental information from external data sources, such as a map to a location discussed in a message. However, such supplementing often fails to reflect the personal context of the content item to the user, who may not easily recall the associated personal context when the content item is later presented. Instead, for a content item to be saved, a device may evaluate personal data sources to identify the personal context of the content item to the user, and add personal context annotations to a content item record of the saved content item. Later, during a presentation of the content item to the user, the personal context annotations may be included as a reflection of the personal context of the content item to the user.

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 aggregator, data processing and networking framework.

Abstract: The present teaching relates to entity extraction and disambiguation. In one example, an entity name extracted from a data source associated with a user is obtained. One or more entity types associated with the entity name are determined. One or more entity candidates are identified with respect to each of the one or more entity types. An entity candidate is selected with respect to one of the one or more entity types to be an individual associated with the entity name.

Abstract: The present teaching relates to recommending content by analyzing the streamed data. A request is received from a user requesting one or more recommendations from a set of items. A first distribution indicative of an interest distribution of the user in a plurality of topics is obtained. For each item, a second distribution indicative of a classification distribution of the item with respect to the plurality of topics is obtained. A score is estimated based on the first distribution and the second distribution, wherein the score indicates likelihood that the user is interested in the item. The scores associated with the set of items are ranked. The one or more recommendations are presented based on the ranked scores.