Abstract: The present teaching, which includes methods, systems and computer-readable media, relates to providing content from multiple disparate sources including a person's personal data sources and non-personal data sources. The disclosed techniques may include receiving a request for content from a person; obtaining first content from a first source private to the person based on the request; obtaining second content from at least one second source based on the request; blending the first content from the first source and the second content from the at least one second source to generate a blended content; and providing the blended content to the person in response to the request.

Abstract: Entity profile information is presented to a user of a computing device. In one embodiment, a method includes: receiving a communication associated with a first entity; in response to receiving the communication, creating or updating, by at least one processor, a first entity profile, wherein the first entity profile is for display to the user on the computing device; and storing a plurality of entity profiles for entities, the entity profiles including the first entity profile.

Abstract: The present teaching generally relates to detecting data bucket discrepancies associated with online experiments. In a non-limiting embodiment, a monitoring layer may be generated within an online experimentation platform that includes at least a first layer, and where a first online experiment is associated with the first layer, the monitoring layer includes a monitoring layer data bucket, and the first layer includes at least a first data bucket. First data representing user activity associated with a first plurality of identifiers may be obtained, the user activity being associated with the first layer. Second data representing at least one user engagement parameter may be generated, and a first discrepancy between the first and second data may be determined. The first discrepancy indicating a first amount of identifiers that include a first metadata tag associated with the first layer and lack a second metadata tag associated with the monitoring layer.

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: Users consume a wide variety of content from various sources, such as videos accessible through websites. As provided herein, content recommendations that are contextually and/or semantically relevant to current content consumed by a user may be identified and provided to the user. For example, metadata for a video being watched by the user may be identified (e.g., terms extracted from a description, user reviews, a category, and/or other information). The metadata may be used to identify content recommendations based upon the metadata corresponding to terms grouped into a set of refined topic groupings of a graph comprising terms and relationships between terms extracted from a content corpus. The metadata may be matched to relevant terms within the set of refined topic groupings, and content recommendations comprising content corresponding to the relevant terms may be suggested to the user.

Abstract: Methods, systems, and computer-readable media are disclosed for dynamic partitioning in distributed computing environments. One method includes: receiving a first data set and a second data set; mapping the first data set into a first set of key-value pairs; mapping the second data set into a second set of key-value pairs; estimating, using a sketch, a frequency count for each key based on the first set of key-value pairs and the second set of key-value pairs; determining whether the estimated frequency count for each key is greater than or equal to a predetermined threshold; and partitioning the key when the estimated frequency count for the key is greater than or equal to the predetermined threshold.

Abstract: Embodiments are directed at determining a conversion rate and a latency distribution for an online campaign. The conversion rate indicates a ratio of an overall number of converted impressions to the number of previously provided impressions. The converted impressions are a subset of the set of previously provided impressions. One method includes receiving conversions from the campaign and determining an observed latency for the conversions. Each conversion is uniquely associated with one of the converted impressions. The observed latencies are based on a temporal difference between the conversion and the associated converted impression. The method simultaneously determines each of the conversion rate and parameters of the latency distribution. The latency distribution indicates a temporal distribution of the observed latencies.

Abstract: A method, implemented on at least one computing device each of which has at least one processor, storage, and a communication platform connected to a network for providing synthetic answers to a personal question is disclosed. A personal question is received from a person. One or more entities are extracted from the personal question. One or more relations are extracted from the personal question. A model is selected based on the personal question. One or more synthetic answers to the personal question are obtained based on the one or more entities, the one or more relations, and the selected model.

Abstract: One or more computing devices, systems, and/or methods for generating presentations based upon articles are presented. For example, an article may be selected from one or more article databases. Content items may be extracted from the article, wherein the content items comprise one or more videos, one or more images and/or one or more social media posts. Text of the article may be analyzed to generate a plurality of text segments. A presentation, comprising a plurality of slides, may be generated based upon the content items and the plurality of text segments. A graphical user interface of a client device may be controlled to display a presentation editing interface comprising a representation of the presentation. One or more inputs, corresponding to one or more edits to the presentation, may be received via the presentation editing interface. An edited presentation may be generated based upon the one or more inputs.

Abstract: The present teaching generally relates to detecting abnormal user activity associated with an entity. In a non-limiting embodiment, baseline distribution data representing a baseline distribution characterizing normal user activities for an entity may be obtained. Information related to online user activities with respect to the entity may be received, distribution data representation a dynamic distribution may be determined based, at least in part, on the information. One or more measures characterizing a difference between the baseline distribution and the dynamic distribution may be computed, and in real-time it may be assessed whether the information indicates abnormal user activity. If the first information indicates abnormal user activity, then output data including the distribution data and the one or more measures may be generated.

Abstract: The present teaching relates to request management and data recovery in a data system. In one example, a failure in connection with first data is detected at a first node in a data system. Information associated with a most recent transaction related to the first node is obtained from the persistent storage. Each of other nodes in the data system is requested to transmit one or more transaction requests previously sent to the first node after the most recent transaction. The one or more transaction requests are received from at least one of the other nodes. A sequence of one or more transactions associated with the one or more transaction requests is determined. The one or more transactions are executed according to the sequence in order to recover the first data at the first node.

Abstract: Disclosed are systems and methods for generating recommendations to users based on historical travel information and electronic communication data. The disclosed systems and methods provide a novel framework for automating the transmission of electronic travel-related recommendations to users by consistently monitoring electronic messages received at an electronic communication mailbox corresponding to a user. The disclosed framework operates by leveraging historical user data, data parsed from electronic communication mailbox corresponding to a user, or various vendor information, and using the aforementioned data as inputs for travel-related recommendation models, in order to generate and transmit the optimal travel-related recommendations to a user.

Abstract: Method, system, and programs for measuring user engagement. In one example, a model generated based on user activities with respect to a plurality pieces of content is obtained. One or more actual occurrences of the user activities with respect to one piece of the plurality pieces of content are identified. One or more future occurrences of the user activities with respect to the piece of content are estimated based on the model. A user engagement score with respect to the piece of content is calculated based on the one or more actual occurrences of the user activities and the one or more future occurrences of the user activities.

Abstract: Systems and methods are disclosed for determining an engagement level of a user interacting with an electronic program, comprising receiving or determining a decision node tree, each node in the decision node tree corresponding to a user decision point in the electronic program, determining a number of levels in the decision node tree, determining a user traversed count comprising a number of levels the user has traversed in the decision node tree, and determining the engagement level of the user with the electronic program based upon the user traversed count and the number of levels in the decision node tree.

Abstract: One or more computing devices, systems, and/or methods for generating augmented videos are provided. First coordinates, of a first video frame of a video, may be determined for projection of a graphical object. A first plurality of keypoints on the first video frame may be determined based upon a set of objects. A second plurality of keypoints on a second video frame may be determined. A keypoint of the second plurality of keypoints may correspond to a keypoint of the first plurality of keypoints. A relationship between the first video frame and the second video frame may be determined based upon the first plurality of keypoints and the second plurality of keypoints. Second coordinates of the second video frame may be determined based upon the first coordinates and the relationship. The graphical object may be projected onto the second video frame based upon the second coordinates.

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: 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: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, 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 disclosure provides a novel, computerized framework for automatically selecting the most definitive, precise and high-quality content files corresponding to POIs. The disclosed systems and methods utilize the performance of visual comparisons with a set of definitive content files of a given POI, and by incorporating visual aesthetic features as a factor of such comparisons, a search result is identified that down-weights imprecise and poor quality content files of a given POI, and ensures that only high quality, accurate content files are selected or identified.

Abstract: Disclosed are systems and methods for extracting content based on image analysis. A method may include receiving content including at least an image depicting a coupon; converting the received content into a larger image including the image depicting the coupon; determining, utilizing one or more neural networks, the image depicting the coupon within the larger image, wherein determining the image depicting the coupon comprises: segmenting a foreground bounding box including the image depicting the coupon from background image portions of the image; cropping the larger image based on the bounding box, wherein the cropped image consists of the image depicting the coupon; determining text included in the cropped image; and extracting information included in the coupon based on the determined text.

Abstract: Briefly, embodiments disclosed herein relate to image cropping, such as for digital images, for example.