Abstract: A client application sends an application programming interface call to an interface of a content management system. The call specifies one or more content item search criteria. Sending the call causes the content management system to perform a lookup in a content item index to identify at least one content item that satisfies the one or more content item search criteria. Based on sending the call, the client application receives from the content management system a suggestion to attach the at least one content item to a text being displayed by at the computing system.

Abstract: A database system detects a query targeting a first database object stored in a unified persistence format in a persistence store. In response to detecting the query, the database system determines whether to load the first database object in column-loadable format or page-loadable format into an in-memory store. In response to determining to load the first database object in the column-loadable format, the database system determines if a first bit representation of one or more corresponding primitives in the persistence store is compatible with a second bit representation used for storing the primitives in the in-memory store. The database system performs a native copy operation to copy the primitives from the persistence store to the in-memory store if the bit representations are compatible, where the native copy operation involves copying the primitives on a page-by-page basis without decoding and encoding values of the one or more primitives.

Abstract: Interruptions in an ordered replication stream can be received from in a database. A database instance of the ordered replication stream may detect missing log records and then evaluate log records that are subsequently received to determine whether to update a portion of an in-memory data structure for performing database requests using a comparison of sequence numbers of the last update corresponding to the portion of the in-memory data structure indicated in the log record and the last update recorded for the portion of the in-memory data structure. For comparison indicating valid portions, the log record can be used and for comparison indicating invalid portions, the portion of the in-memory data structure can be made unavailable.

Abstract: Data characterization techniques in an information processing system environment are disclosed. In one example, at least one processing device is configured to obtain data associated with execution of at least one of a plurality of applications in an information processing system. The processing device extracts features from the obtained data, and then selects a reduced subset of features from the extracted features for use in a machine learning classification process configured to determine an intent of the obtained data.

Abstract: A method for detecting and/or localizing keyboard accessibility failures (KAFs) in a web page is disclosed. A document object model of a web page is read. A keyboard navigation flow model is generated from the document object model of the web page based on interactions of a user with the web page. The model includes states representing user interfaces displayed by the web page, nodes representing keyboard inputs in the states, and edges representing transitions that occur in the web page between the nodes. KAFs are detected based on an analysis of the keyboard navigation flow model. A report of the detected one or more KAFs on the web page is produced. The KAFs include unintuitive navigation failures, reflow related failures, and dialog related failures.

Abstract: An apparatus for generation of an integrated data file, wherein the apparatus includes at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to receive content data from a user, receive preference data from the user as a function of receipt of the content data, create a plurality of templates as a function of the preference data and the content data, receive user feedback associated with the plurality of templates, generate one or more updated templates as function of the user feedback and the plurality of templates, generate an integrated data file as a function of one or more updated templates and transmit the integrated data file to one or more content producers.

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: 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 data processing and analysis system that optimizes the resources to be used for data storage and refresh events. A partitioner module for a data analysis system can receive a first client criteria and a first client dataset that includes tabular data and calculate scores that are used to generate partitioning strategies. The selected partitioning strategy can be implemented to produce aggregated data that can be stored in an intelligent data mart. The partitions can then be accessed by a data visualization platform for intelligent, dynamic responses to user requests for data analyses and generation of visualizations. By providing synchronous partitioning of data (especially big data) and intelligent refresh, the data can move from the back-end to the front-end with minimal user clicks and minimal latency in performance.

Abstract: A content collaboration platform, such as described herein, may include dynamic object tables that are configured to dynamically populate and/or update. Dynamic object tables may be configured to retrieve content (e.g., page content) from the content collaboration platform and automatically populate attributes from that content directly in the cells of the dynamic object tables. Updates to the page content may also be automatically updated within the table. In some examples, the dynamic object tables may be embedded within pages of the content collaboration platform and, within the same page, the user can edit, filter, and sort the dynamic object table without toggling to other tabs, applications, or documents.

Abstract: Disclosed are a semantic matching and retrieval method and apparatus. The semantic matching and retrieval method includes steps of obtaining both the vector representation of a query text and the vector representation of a document text; obtaining the final vector representation of the query text; obtaining the final vector representation of the document text; calculating, based on the final vector representation of the query text and the final vector representation of the document text, the similarity score between the query text and the document text; and selecting, based on the similarity scores between the query text and a plurality of document texts, a document text matching the query text from the plurality of document texts.

Abstract: An improved search engine is disclosed. The search engine receives search queries from client devices and inputs these queries into a first neural network (an action understanding model) that includes an action embedding layer. The action embedding layer can be a word embedding layer constructed using action terms. The action understanding model outputs a filter match associated with a type of filter and, in some scenarios, an action-condition pair. The action-condition pair includes an action associated with the type of filter and a condition comprising an adaptive value associated with the action. Based on the filter and, if present, action-condition pair(s), the embodiments generate a structured query and issue the structured query to a data repository (e.g., database). The search engine then returns a search results page responsive to the search query that includes the results returned by the data repository in response to the structured query.

Abstract: A database management engine provides a user interface that allows users to access and modify employee information in a database. The database includes entries for employees, and each database entry includes identifying information about the associated employee. A user can request to modify data within database entries, for instance in order to update information associated with an employee. Responsive to the request, the database management engine identifies liabilities associated with the database modification stemming from associated tax laws. Based on the identified tax liabilities, the engine computes the aggregate tax liability owed by the employer and/or employee. Before modifying a database entry, the engine modifies the user interface to include interface elements detailing the computed aggregate tax liability. The user explicitly can be required to confirm the database modification in view of the aggregate tax liability.

Abstract: Embodiments of copypasta filtering system technologies cluster digital content items into copypasta clusters, extract a first feature set from the digital content items in the copypasta clusters, apply a first set of filters to the first feature set, and based on output of the first set of filters, divide the copypasta clusters into first intent copypasta clusters and possible second intent copypasta clusters. A second feature set is extracted from the digital content items in the possible second intent copypasta clusters. A second set of filters is applied to the second feature set. Based on output of the second set of filters, second intent copypasta clusters are created.

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: An assigned subgroup that includes a plurality of entries is traversed by a prefetcher. It is determined that an expected number of entries associated with the assigned subgroup have been traversed. In response to determining that expected number of entries associated with the assigned subgroup have been traversed, it is determined that a last read entry associated with the assigned subgroup does not correspond to a last entry associated with the assigned subgroup. The prefetcher is preempted by stopping the prefetcher from obtaining a list of entries associated with a remaining portion of the assigned subgroup.

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: A computer-implemented method for operating a technical device with the aid of a multi-dimensional characteristic map. The characteristic map is defined by data points, to each of which a characteristic field value is assigned. For reading out the characteristic map, an output value is determined, as a function of an input variable point to be evaluated for the technical device, with the aid of one-dimensional basis functions, which are assigned to each dimension of a data point. The function values of the one-dimensional basis functions respectively have a monotone curve to a neighboring data point, which has the function value 0, and are outside of the neighboring data point 0. The technical device is operated as a function of the output value.

Abstract: A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.

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.