Abstract: The present disclosure provides for predictive query processing for complex system lifecycle management by identifying a seed document including natural language text describing an issue with a complex system; creating a synthesized document for the seed document by: removing portions of the seed document determined to satisfy filtering rules; identifying a first term set included in the natural language text that map to terminology identified in a data dictionary; extracting term-order data based on locations of the first term set in the natural language text; and including the first term set and the term-order data in the synthesized document; identifying, from a corpus of historic electronic documents, a first document set that are related to the seed document based on the term-order data included in the synthesized document; and outputting at least a portion of the first set of historic electronic documents.

Abstract: A mechanism is provided in a data processing system for presentation delivery. The mechanism delivering a presentation content to a group of users and receives a plurality of questions concerning the presentation content from the group of users. The mechanism stores the plurality of questions in a question history database and clusters the plurality of questions in the question history database into one or more question clusters. The mechanism determines a topic for each of the one or more question clusters to form one or more question topics and generates feedback for updating the presentation content based on the one or more question topics.

Abstract: A system for alimentary instruction sets derived from artificial intelligence systems for vibrant constitutional guidance, as derived using one or more machine-learning procedures from training data relating prognostic and ameliorative labels. A physical performance instruction set is derived from the alimentary instruction sets using one or more physical performance entity profiles.

Abstract: A system for classification to prognostic labels includes a classification device configured to receive a first training set including a plurality of first data entries, each including at least an element of physiological state data and at least a correlated first prognostic label and a second training set including a plurality of second data entries, each including at least a second prognostic label and at least a correlated ameliorative process label, to record at least a physiological test sample, and to transmit the prognostic and ameliorative outputs to a user device. The system includes a prognostic label learner configured to generate the prognostic output as a function of the first training set and the physiological test sample and an ameliorative process label learner configured to generate the ameliorative output as a function of the second training set and the prognostic output.

Abstract: A method, an apparatus, an electronic device, and a computer storage medium for accessing raster data are provided. The raster data access method comprises: executing a corresponding window query input to determine a target pixel resolution corresponding to a query window according to a raster data access request; calculating a sampling level according to the target pixel resolution and a stored pixel resolution of a raster object, and determining whether the sampling level is greater than a threshold; and accessing raster data corresponding to the query window according to a column-level index if the sampling level is greater than the threshold, the column-level index being an index generated by down-sampling according to raster data of the raster object in a column. Using the raster data access method can achieve quick access to raster data.

Abstract: A system for an artificial intelligence fitness professional support network for vibrant constitutional guidance includes a computing device configured to obtain at least a biological extraction from a user, receive a user request, determine a fitness regimen, wherein determining the fitness regimen further comprises generating a diagnostic output as a function of the at least a biological extraction, and determining the fitness regimen as a function of the user request and the diagnostic output, and output the fitness regimen.

Abstract: Writers participating in a backup are identified. A mapping is generated between the writers and associated files. The mapping includes file properties. The mapping is initialized by tagging the writers with a full backup tag. A base backup copy of the writers is created by conducting a full backup of each writer tagged with the full backup tag. At a current backup operation after creating the base backup, a list of current files that will participate in the current backup operation is generated. The list of current files is compared against the files in the mapping to determine whether a particular writer associated with a current file should be tagged with the full backup tag or an incremental backup tag. The particular writer is tagged with the incremental backup tag when file properties associated with the current file have changed.

Abstract: In some implementations, a device may receive an indication of an item associated with a user and a first entity and may store information associated with the item in a first entry of a first database associated with the user. The device may identify a second entry in a second database associated with the first entity. The second entry may identify one or more documents associated with the item, and the second database may identify documents for a second set of items associated with the first entity. The device may map the first entry to the second entry to enable the one or more documents associated with the item to be associated with the first entry of the first database associated with the user. The device may transmit an indication of at least one document of the one or more documents.

Abstract: A computing device includes a processor and a machine-readable storage storing instructions. The instructions are executable by the processor to: receive a bit vector representing input data to be tokenized; divide the bit vector into two vector portions; and perform a plurality of rounds of a Feistel network on the two vector portions, each round including converting one vector portion using a table-based hash function that combines multiple tokens retrieved from at least one token table.

Abstract: A system can collapse steps into an aggregate step to simplify analysis while maintaining underlying data that forms each of the steps collapsed into the aggregate step. The steps may or may not be related in a sequence or grouping of steps. The aggregate step may be a new step that comprises the data of the individual steps used to form the aggregate step. Alternatively, the aggregate step may be a virtual step that may reference or link to the steps used to form the aggregate step, but may not include the data itself. By forming aggregate steps, filtering and notification generation can be simplified. Further, extraneous data can be collapsed into a single aggregate step, which can be particularly advantageously when analyzing large data sets.

Abstract: Expanded encoding may be implemented to enhance regular expression filter capabilities. Two or more adjacent characters in a stream of characters to be processed by a regular expression filter may be recognized and replaced with a symbol. The symbol may be used instead of the two or more adjacent characters for processing through non-deterministic finite automaton (NFA) states. The output of the NFA states may indicate whether a match for a regular expression is present in the stream of characters.

Abstract: A hashing apparatus includes a memory and circuitry. The memory stores (i) multiple hash tables storing associative entries, each including at least one entry key and a respective value, the hash tables are associated with respective different hash functions, and an associative entry is accessible by applying the relevant hash function to a key matching an entry key in the associative entry, and (ii) an affinity table that stores table-selectors for selecting hash tables with which to start a key lookup. The circuitry receives a key, reads from the affinity table, by applying an affinity function to the key, a table-selector that selects a hash table, accesses in the selected hash table an associative entry by applying the hash function associated with the selected hash table to the key, and in response to detecting that the key matches an entry key in the associative entry, outputs the respective value.

Abstract: There is provided a method and a server for retraining a machine learning algorithm (MLA), the MLA having been trained to classify documents based on features thereof. A resource having a plurality of content items submitted by users is accessed. At least one content item associated with a document having been presented as a search result by a search engine server in response to a search query is identified. The at least one content item is analyzed based on a set of features to determine if the document has been misclassified by the MLA in response to the search query. In response to determining that the document has been misclassified, a training object is generated based on the misclassified document. Other misclassified documents are identified in a similar manner to obtain a set of training objects. The MLA is then retrained based on the set of training objects.

Abstract: Systems and methods are described herein to search for content recommendations, and in particular, for generating emoji-based metadata for content and processing an emoji-based query using the emoji-based metadata. A system may receive a query comprising a text portion and an emoji portion. A system may search a database to identify content items associated with the query based on the text portion and the emoji portion, wherein the searching based on the emoji portion is based at least in part on matching emojis associated with a content item. A system may retrieve, for each of the content items, an emoji match score based on the emoji portion and a textual match score based on the text portion. A system generates, for each of the content items, a respective aggregate score based on the respective emoji match score and textual match score. A system may generate for display representations of the content items ordered according to the respective aggregate scores.

Abstract: Embodiments facilitating data exploration in a computing environment by a processor. A multidimensional dataset may be received. The multidimensional dataset may be processed according to booting operation parameters. A visualization and exploration of an interactive representation of one or more probabilistic models for each one of a set of instances using the multidimensional dataset.

Abstract: An embodiment of the present invention is directed to implementing an open policy agent bridge to entitlements determination as they relate to market data. According to an embodiment of the present invention, Open Policy Agent (OPA) may be implemented as a policy engine to make decisions and determinations concerning fine-grained access control for an application.

Abstract: An approach is provided for optimizing a database buffer pool. Based on statistics about read and write operations in a range of pages, the range of pages is determined to be a candidate for a hot read range for which locks and latches are avoided in processing operations in the hot read range. Using an on-time trigger or pre-trigger process, the hot read range is created from the range of pages by marking start and end points in the range of pages. Write operation(s) are determined to be included in the hot read range by marking an object control block. The write operation(s) are added to a write pending list. The read operations in the hot read range are performed without a latch or lock. The write operation(s) are merged from the write pending list to the range of pages and the write operation(s) are performed.

Abstract: An analytics engine (AE) computing system for analyzing and evaluating data in real-time associated with a performance of parties interacting within a multi-party interaction is provided. The AE system is configured to receive interaction data from a data validation (DV) computing device, retrieve contextual data from a contextual data source, determine a task identifier, and calculate a task score. The AE system is also configured to retrieve normalization model data from a normalization database, compare a plurality of normalization rules to the validated interaction data and the contextual data, and determine at least one normalization factor applies to the task score. The AE system is further configured to normalize the task score based on the at least one normalization factor, calculate an aggregate score using the normalized task score, and store the validated interaction data, the normalized task score, and the aggregate score in an analysis database.

Abstract: According to an embodiment, a method of building a database in which voice signals match texts comprises providing a captcha-purposed voice signal including a first voice signal matched with a first text and a second voice signal matched with no text, sending a request for a first input text and a second input text for the captcha-purposed voice signal, when the first input text and the second input text are received, comparing the first text with the first input text, and when the first text is identical to the first input text, matching the second voice signal with the second input text and storing the match. Embodiments of the present invention may be related to artificial intelligence (Al) modules, unmanned aerial vehicles (UAVs), robots, augmented reality (AR) devices, virtual reality (VR) devices, and 5G service-related devices.

Abstract: A data processing system implements receiving a request for user-centric topic recommendations from a computing device of a user in response to a user input in an application indicating that the user is attempting to assign a tag to a first content item in the application; obtaining a first set of user-centric topic recommendations from a first topic datastore based on a relevance ranking assigned to each of the topic recommendations; providing the first set of user-centric topic recommendations to the computing device; causing the computing device to display the first set of user-centric topic recommendations; receiving one or more second requests for user-centric topic recommendations; obtaining one or more second sets of user-centric topic recommendations from the first topic datastore based on the query string and the relevance ranking; and causing the computing device of the user to display the one or more second sets of user-centric topic recommendations.