Abstract: Systems and methods for matching videos to podcast episodes are provided. A data store comprising podcast episode identifiers is accessed. The podcast episode identifiers are associated with one or more podcast episode attributes. A video content item is identified. The video content item includes one or more video content item attributes. A matching podcast episode identifier that matches the video content item is determined based on the one or more podcast episode attributes and the one or more video content item attributes. A ranking of one of the video content item or the matching podcast episode identifier is caused to be adjusted to reflect the correspondence between the video content item and the matching podcast episode identifier. Information associated with the matching podcast episode identifier is provided to a first user device.

Abstract: A method for automatic metadata tag identification for videos is described. Content features are extracted from a video into respective data structures. The extracted content features are from at least two different feature modalities. The respective data structures are encoded into a common data structure using an encoder of a recurrent neural network (RNN) model. The common data structure is decoded using a decoder of the RNN model to identify content platform metadata tags to be associated with the video on a social content platform. Decoding is based on group tag data for users of the social content platform that identifies groups of the users and corresponding group metadata tags of interest for the groups of users.

Abstract: A method including determining neighboring items from among sample items based on a respective embedding distance between a query image of a query item and a respective image of each of the neighboring items. The each of the sample items can comprise the respective image and at least one respective item label. The method further can include determining a respective normalized weight for each of the neighboring items based on the respective embedding distance between the query image and the respective image of the each of the neighboring items. The method also can include determining a query item label of the query item based on a weighted majority vote by the neighboring items via the respective normalized weight for the each of the neighboring items. Other embodiments are disclosed.

Abstract: Systems and methods directed to returning personalized image-based search results are described. In examples, a query including an image may be received, and a personalized item embedding may be generated based on the image and user profile information associated with a user. Further, a plurality of candidate images may be obtained based on the personalized item embedding. The candidate images may then be ranked according to a predicted level of user engagement for a user, and then diversified to ensure visual diversity among the ranked images. A portion of the diversified images may then be returned in response to an image-based search.

Abstract: The present invention is a computer-implemented system and method for creating a user profile based on multimedia files. The method includes storing multimedia files associated with one or more users in at least one computing device. The method includes obtaining content data from the multimedia files stored in the computing device through a content extraction module. The content extraction module performs steps to obtain the content data from multimedia files. A mobile application accesses the files stored in the computing device. Files are extracted and processed by utilizing one or more machine learning algorithms and retrieving content data and file metadata for each multimedia file from the processed data. Content-based user attributes are created by analyzing the aggregated content data and file metadata, Content-based user attributes are transmitted to an application server and stores the content-based user attributes to a user profile database.

Abstract: An approach for optimizing storage on a local storage device. The approach identifies a stored or being stored on a user's local storage device. The approach extracts metadata from the media file. The approach searches the user-associated storage locations for a matching media file based on the metadata. If the approach locates the matching media file, then the approach, using artificial intelligence (AI), predicts if the local device storage should be optimized for the media file, then the approach, using AI, stores a link to the matching media file on the local device storage and removes the media file from the local device storage.

Abstract: Systems, methods, and non-transitory computer readable media with instructions for methods here may be used to create and render interactive charts using large amounts of data, by efficiently dividing up the storage and processing of the data between a networked side and a local application side. In certain example embodiments, these two sides work in conjunction with one another, alternatively or additionally, in certain example embodiments, they may act independently and/or alone. The resulting charts may then be used by being embedded in external web pages.

Abstract: The present disclosure provides a technical solution of multi-modal chatting, which may provide response to user query by using multi-modal response in the interaction between chatbot and human beings, so that the expressing ways and the expressed content by the chatbot could be richer by using such response in a multi-modal way.

Abstract: A computer-implemented method, computer program product, and computer system for accessing content on a web page. The method accesses a displayed web page in a web browser of a user computing device and receives a search term for content within the web page. The method accesses contextual information held locally on the user computing device and scans the web page to identify one or more portions of content of the web page relevant to the search term and the contextual information. The method provides a display on the user computing device with links to the relevant web page content.

Abstract: Classifying and filtering data by categorizing a portion of a data segment according to the content of the portion, correlating each portion with a user content preference dictionary, assigning a content weight to each portion according to the correlation, and masking content portions having a weight below a threshold value.

Abstract: A system for managing industrial enterprise (IE) data models may include a storage device storing instructions and IE data models. Each of the IE data models may include references to artifacts and a directed graph having nodes and edges. Each of the nodes may represent a respective one of the artifacts. Each of the edges may indicate a relationship between a respective pair of the artifacts. The system may also include a processing device operable to execute the instructions to perform operations including managing dataflow through a particular one of the data models, wherein the edges of the directed graph of the particular data model define a direction of propagation of data through the artifacts of the particular data model, and providing version control functionality for the plurality of data models and for the artifacts referenced by any of the plurality of data models.

Abstract: An operation method of a user terminal for providing a video slide service includes uploading a UGC video to a server; receiving, from the server, scene meta-information for each playback section of the UGC video; generating a video slide file on the basis of the received scene meta-information for each playback section; classifying, according to categories, a plurality of pieces of page information configuring the video slide file; and generating a storybook corresponding to the UGC video on the basis of a plurality of page groups classified according to the categories.

Abstract: A method, apparatus, and computer-readable storage medium that generate, from a database, an identifier record grouping including the identifier record and at least one other identifier record, generate one or more strength indicators of the generated identifier record grouping, normalize a value of each of the one or more strength indicators based on an average value associated with the respective strength indicator, generate a value of a strength metric of the generated identifier record grouping based on a sum of the normalized values of the one or more strength indicators, rank the value of the strength metric amongst values of strength metrics associated with a plurality of identifier record groupings within the database, and determine a strength score of the generated identifier record grouping as the strength score of the identifier record based on the ranking.

Abstract: A method for soil data interpolation includes collecting first and second agricultural field point data values corresponding to a variable grid and generating interpolated point data values by analyzing the first and second agricultural field point data values. A computing system includes a processor and a memory storing instructions that, when executed by the processor, cause the computing system to collect first and second agricultural field point data values corresponding to a variable grid and generate interpolated point data values by analyzing the first and second agricultural field point data values. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to collect first and second agricultural field point data values corresponding to a variable grid and generate interpolated point data values by analyzing the first and second agricultural field point data values.

Abstract: A computer-implemented method for searching for a similar image in an image database includes receiving a query image, computing a value of a similarity measure of the query image, comparing the value of the similarity measure of the query image with metadata of the partitions, discarding at least one partition of the image database based on the comparison of the value of the similarity measure of the query image with the metadata, comparing the images of at least one of the remaining partitions with the query image, and selecting at least one image of the at least one partition of the remaining partitions as the similar image based on the comparison of the images of the at least one of the remaining partitions with the query image.

Abstract: Aspects relate to apparatuses and methods for using machine learning to classify a user to a posting. An exemplary apparatus includes at least a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to acquire a plurality of user inputs from a user, acquire a plurality of posting inputs from postings, associate each posting input of the plurality of posting inputs to a posting category, compare the plurality of user inputs to the plurality of posting inputs, and classify the user to a posting category as a function of the comparison.

Abstract: The system generates a recommendation of content for use in collaboration, allowing relevant content to be used as base content. The system identifies a content item, and retrieves reviews for the content item from one or more sources or forums. The system filters the reviews to generate a reduced set of reviews based on text of the respective reviews, profile information associated with the reviews, and reference information. A recommendation metric is determined for the content item based on the reduced set of reviews and based on the one or more recommendation criteria. The recommendation criteria specify which aspects of the content impact recommendation, and how those aspects impact recommendation. The recommendation metric indicates whether the content item is recommended as base content, to be used for generating collaborative content. The system generates a recommendation indicator indicative of the recommendation metric, and outputs the indicator for display, storage, or both.

Abstract: A journaling file system may implement remote durable logging. Updates to a file system may be received, and log records describing the updates may be stored in a locally-accessible file system change log. The update may then be acknowledged as committed. The log records may then be sent to be stored in a network-based data store in a remote version of the file system change log. Once it may be determined that the log records are stored in the remote version, storage space for the log records in the local file system change log may be reclaimed. Various types of restoration and duplication techniques may be implemented based on the remote version of the change log to restore a file system at an originating device or to duplicate the file system at a different device.

Abstract: Dynamic determination of video correlation is disclosed, including: obtaining a plurality of recorded video interactions; obtaining a plurality of recorded non-video interactions; storing, at a database, event data determined based at least in part on the plurality of recorded video interactions and the plurality of recorded non-video interactions; and determining a subset of the event data that comprises correlations between a video and non-video interactions.

Abstract: Disclosed is a computer implemented method of creating a profile of a user based on user behavior. The method may include receiving a plurality of Universal Resource Locators (URLs) corresponding to a plurality of webpages visited by the user. Further, the method may include retrieving content from each of the plurality of webpages based on the plurality of URLs. Furthermore, the method may include analyzing content from each of the plurality of webpages. Additionally, analyzing content from a webpage may include analyzing content corresponding to each content type present on the webpage. Further, the method may include identifying a plurality of keywords corresponding to the webpage based on the analyzing. Furthermore, the plurality of keywords may be associated with a plurality of affinity values. The plurality of keywords and the plurality of affinity values may constitute the profile of the user.