Abstract: Methods and systems for selecting and presenting web resources (e.g. videos) are provided, the method includes: transmitting a first video to be played by a device associated with a user account; and during playback of the first video at the device: detecting an update to configuration data associated with the user account; determining, based on the update to the configuration data associated with the user account, a next video recommendation for the user account; and causing an indication of the next video recommendation to be displayed on the device.

Abstract: Systems and methods are provided to process a digital photo and other media. An apparatus to process digital photos can include a tangibly embodied computer processor (CP) and a tangibly embodied database. The CP can perform processing including: (a) inputting a photo from a user device, and the photo including geographic data that represents a photo location at which the photo was generated; (b) comparing at least one area with the photo location and associating an area identifier to the photo as part of photo data; and (c) performing processing based on the area identifier and the photo data.

Abstract: Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.

Abstract: Methods and systems described herein can provide a computing device configured to display on a display screen of the computing device a first window listing a set of entries and a second window that can add entries directly into the set of entries and that can search for entries having selected features. The second window can dynamically display one or more keywords related to an entry as the entry is being created. The keywords can be determined as the entry is created and can be associated with the entry as the entry is added to the set of entries. The second window can receive a search request with the keywords and in response, cause the entries associated with the keywords to be displayed in the first window.

Abstract: Methods, systems, and media for determining a coverage score for a system that receives a stream of requests are provided. In some embodiments, the method includes: for a processing system that receives a stream of requests, determining a first time window in which requests are received by the processing system, wherein the first time window has a start time and an end time and wherein each of the requests is associated with a timestamp; determining a first number of requests that entered the processing system after the start time of the first time window; determining a second number of requests that entered the processing system within the first time window and that were successfully completed within a second time window from the timestamp associated with each of the requests; determining a coverage score that is a ratio of the second number of requests in comparison with the first number of requests; and generating a notification for a user of the processing system based on the coverage score.

Abstract: A data recovery method includes receiving a request to recover target audio and video behavior data generated during use of an audio and video application by a target user. The target audio and video behavior data has been deleted from a database. The method includes obtaining a target data category of the target audio and the video behavior data; searching a blockchain system for the target audio and video behavior data based on the target data category, the blockchain system being configured to store operation data generated by the audio and video application that includes first operation data of audio and video behavior data. The method includes storing the target audio and video behavior data in the database; and returning the target audio and video behavior data to the target user.

Abstract: Techniques and solutions are described for clustering, with reduced memory consumption, observations in a data set. A first observation is received. A distance is determined between the first observation and a first cluster. It is determined that the distance satisfies a threshold, and the first observation is added to a first sample of the first cluster. A first set of means is calculated for the first sample using data of the first observations and data of at least a second observation of the first sample. A second set of means is calculated for the plurality of elements for the first cluster using the first set of means for the first sample and at least a third set of means for at least a second sample of the first cluster. An identifier of the first observation is added to a collection of observation identifiers classified in the first cluster.

Abstract: Systems and methods are provided to process a digital photo and other media. An apparatus to process digital photos can include a tangibly embodied computer processor (CP) and a tangibly embodied database. The CP can perform processing including: (a) inputting a photo from a user device, and the photo including geographic data that represents a photo location at which the photo was generated; (b) comparing at least one area with the photo location and associating an area identifier to the photo as part of photo data; and (c) performing processing based on the area identifier and the photo data.

Abstract: Systems and methods are provided herein for automatically arranging media assets that are contextually related to a requested media asset for access prior to a start time of the requested media asset. In some embodiments, user input circuitry may receive a user request to access a media asset. Control circuitry may identify, by consulting a database, a first set of media assets that share a context with the requested media asset and were released prior to the release date of the requested media asset. Control circuitry may determine a subset of media assets of the first set of media assets by performing a comparison of each media asset of the first set of the media assets against a viewing history of the user. Control circuitry may access a user profile to determine a user constraint, and generate a recommendation for display based on a first aspect of the user constraint.

Abstract: A control method according to the present disclosure includes: receiving, from a terminal operated by a first user who is one of parties that have concluded a first contract, first transaction data that includes a first smart contract corresponding to the first contract and a first electronic signature associated with the first user; executing a consensus algorithm with a plurality of other servers; and recording a block including the first transaction data in a distributed ledger. The first smart contract includes (i) content of the first contract which is a main contract, (ii) a variable that is provisional and used for identifying a second smart contract corresponding to a second contract which is to be newly concluded as a sub contract of the first contract, and (iii) a condition for creation of the second smart contract.

Abstract: A method and system provide the ability to personalize a digital channel. Multiple content assets are obtained and include an image content asset. Each of the assets is associated with an associated set of semantic elements. The multiple content assets are clustered into content clusters based on a similarity of the semantic elements. A first content asset is selected. The clustering is used as a metric to estimate distances between the first content asset and remaining multiple content assets. The remaining multiple content assets are scored based on the distances. One of the remaining multiple content assets is selected based on the scoring and provided for a personalized component of the digital channel. In addition, a coverage map that includes both users and content may be generated based on the clusters and then utilized to select the content asset.

Abstract: Client-based search query autocomplete is disclosed. A search engine server system sends a search web page of a search engine to a content distribution network (CDN) server system for delivery to a client computing device. The search web page includes a query dialog box and an autocomplete service that is configured to present search query suggestions on a display device. The search engine server system receives, from the CDN server system, a search query list request for a predetermined list of search query suggestions, the search query list request originating from the autocomplete service of the search web page executing on the client computing device. The search engine server system sends the predetermined list of search query suggestions to the CDN server system for delivery to the client computing device.

Abstract: A method for training a fusion ordering model, a search ordering method, an electronic device and a storage medium, and related to the technical field of artificial intelligence such as deep learning and the like are provided. The method includes: inputting prediction scores of a plurality of targets included in a candidate search result into a fusion ordering model, to obtain a fusion ordering result; collecting feedback information of the plurality of targets included in the fusion ordering result; and updating the fusion ordering model by utilizing the feedback information and a combined function, wherein the combined function is a function constructed by utilizing the plurality of targets. The solution of the embodiment is favorable for balancing the requirements of the plurality of targets, and the obtained updated fusion ordering model can provide a better search ordering result.

Abstract: A method for querying information includes: acquiring an information query instruction; obtaining a query intention by performing intention identification on the works information query instruction; determining a type of the query intention in a plurality of intention types; obtaining an entity detection result by detecting whether the query intention contains an author entity and a painting entity; acquiring a query result based on the query intention and reference information, wherein the reference information includes the type of the query intention and the entity detection result, and the query result includes at least one information of an image, an audio and a text; and displaying the query result.

Abstract: A device receives user interface interaction data that identifies an interaction that a user has with an interface that displays an image of a vehicle. The device generates, by using a data model to process at least a portion of the image, an array of vectors that includes one or more vectors relating to vehicle characteristics of the vehicle. The device assigns one or more weights to the one or more vectors based on the user interface action data. The device determines, based on a similarity analysis, similarity scores that indicate similarities between the array of vectors that include the one or more vectors that have been weighted and other arrays relating to the vehicles depicted in the images. The device selects a subset of the images based on the similarity scores and causes the subset of the images to be displayed.

Abstract: A mobile device hosts an artificial intelligence model trained for text-based image searches. Images associated with an image album of the mobile device are indexed by generating, based on the artificial intelligence model, image vectors from the images and word vectors from the image vectors. In response to user input that includes text representing a keyword search, a word vector is generated from the text based on the artificial model. A match is determined between the word vector and one or more of the word vectors to generate a search result that identifies one or more images corresponding to the one or more word vectors. The mobile device displays the search result on a user interface.

Abstract: A method of personalized image retrieval includes obtaining a natural language query including a name; replacing the name in the natural language query with a generic term to provide an anonymized query and named entity information; obtaining a plurality of initial ranking scores and a plurality of attention weights corresponding to a plurality of images using a trained scoring model that inputs the anonymized query and the plurality of images; obtaining a plurality of delta scores corresponding to the plurality of images using a re-scoring model that inputs the plurality of attention weights and the named entity information; and obtaining a plurality of final ranking scores by modifying the plurality of initial ranking scores based on the plurality of delta scores. The trained scoring model performs semantic based searching and the re-scoring model determines a probability that faces detected in the plurality of images correspond to the name.

Abstract: Methods, systems and computer program products are provided for spoiler prevention. Media consumption applications may be placed in “spoiler-free” mode, for example, to prevent media content from spoiling first-hand user experience. A user may provide and/or authorize access to and use of spoiler prevention information. A user may request media content (e.g., while surfing the Internet). Digital media content to be presented to a user may be searched in real-time and/or pre-searched for spoiler content and/or associated spoiler indications relative to spoiler prevention information. Identified spoiler content may be concealed from users. A procedure may be provided for users to determine one or more reasons why content is concealed, to selectively reveal concealed content, and to provide feedback whether concealed content was or was not spoiler content for a user. Feedback may be used to improve spoiler prevention, for example, by retraining a machine learning model, which may be user-specific.

Abstract: Systems and methods are provided to process a digital photo and other media. An apparatus to process digital photos can include a tangibly embodied computer processor (CP) and a tangibly embodied database. The CP can perform processing including: (a) inputting a photo from a user device, and the photo including geographic data that represents a photo location at which the photo was generated; (b) comparing at least one area with the photo location and associating an area identifier to the photo as part of photo data; and (c) performing processing based on the area identifier and the photo data.

Abstract: Systems and methods for training a machine learning (ML) ranking model to rank genealogy hints are described herein. One method includes retrieving a plurality of genealogy hints for a target person, where each of the plurality of genealogy hints corresponds to a genealogy item and has a hint type of a plurality of hint types. The method includes generating, for each of the plurality of genealogy hints, a feature vector having a plurality of feature values, the feature vector being included in a plurality of feature vectors. The method includes extending each of the plurality of feature vectors by at least one additional feature value based on the number of features of one or more other hint types of the plurality of hint types. The method includes training the ML ranking model using the extended plurality of feature vectors and user-provided labels.