Abstract: Techniques for creating and executing custom AI-driven actions in a data analysis interface are disclosed. One or more embodiments receive user input that defines a custom action by specifying an AI prompt with a natural language query and context variables. This definition is stored for later use. One or more embodiments present a graphical user interface (GUI) displaying data items, allowing users to select a subset. Based on the stored definition of a custom action, an option to execute the custom action appears. When the option is chosen, one or more embodiments assign metadata values from the selected items to the context variables, creating initialized context variables. The complete prompt, including the query and initialized variables, is submitted to an AI agent. The AI's response is displayed in the GUI, providing context-aware insights within the data analysis workflow.

Abstract: Embodiments of the present disclosure relate to a document sharing method and apparatus, a device, and a medium. The method is applied to a first client and includes: receiving a follow trigger operation for a target document, where the target document is synchronously displayed on the first client and a second client; determining a second trigger position of the follow trigger operation relative to the target document based on a first trigger position of the follow trigger operation relative to a first screen and a first document position of the target document on the first screen; and sending the second trigger position to the second client, such that the second client displays, on a second screen based on a second document position of the target document on the second screen and access address information of the target document, content in the target document that corresponds to the second trigger position.

Abstract: Changes made to a database table are accumulated, in durable storage, and snapshots of partitions of the table are obtained. For successive snapshots of a partition, the system accesses a previous snapshot, applies changes from the accumulated changes, and stores the updated snapshot to a durable data store. The accumulated changes and the successive partition snapshots are made available to restore the database to any point in time across a continuum between successive snapshots. Although each partition of the table may have a backup snapshot that was generated at a time different from when other partition snapshots were generated, changes from respective change logs may be selectively log-applied to distinct partitions of a table to generate an on-demand backup of the entire table at common point-in-time across partitions. Point-in-time restores of a table may rely upon a similar process to coalesce partition snapshots that are not aligned in time.

Abstract: This disclosure provides a method, device and a computer program product for managing metadata of a file system. The method may include: determining a data structure of the metadata based on a type of the file system; deriving a reference value for a first field of the metadata based on the data structure of the metadata and a protocol of the file system; and overwriting the first field of the metadata with the reference value in response to an actual value of the first field of the metadata being not equal to the reference value and there being no backup for the metadata.

Abstract: Pattern matching for human readable prime number compression (HRPNC), including: identifying, in a binary object, one or more portions of the binary object matching one or more patterns; performing HRPNC on each portion of the one or more portions to generate one or more compressed portions; and generating, for the binary object, a compressed binary object comprising a concatenation of the one or more compressed portions.

Abstract: Metadata about files present at clients is collected. The metadata includes values for a set of features associated with the files. The values are normalized and centroids are calculated. For each file, a comparison is performed of a normalized value of a feature associated with a file against a respective centroid calculated for the feature. Based on the comparison, the file is or is not backed up. A machine learning model is applied to files that have been backed up to tier the backed up files.

Abstract: A request to update a database system based on a natural language input document may be received. An input metadata extraction prompt may be determined based on the natural language input document and a prompt template including a fillable portion. The input metadata extraction prompt may be determined at least in part by filling the fillable portion with natural language input text selected from the natural language input document. The prompt template and the input metadata extraction prompt may each include natural language instructions to generate novel text identifying data values characterizing the natural language input document and corresponding to one or more database fields in the database system. A completed metadata extraction prompt may be determined by executing the natural language instructions via a generative language model to generate the novel text. A database query updating the database system may be determined based on the novel text.

Abstract: Systems and methods for improving query creation and AQM are provided. A user interface is provided that allows an analyst to generate and test queries. After the analyst provides a query, one or more subsets of previous call center interactions are selected to test the provided query using methods such as a large language model or string vectorization. Once the subsets of interactions are selected, an LLM is used to evaluate the query against the subset. The evaluations may indicate interactions which were positive and which interactions were negative and may include quotes from the interactions that support the evaluations. The evaluations are presented to the analyst for review, and the analyst may revise the query in view of the evaluations. Once the analyst is satisfied with the performance of the query, the query may be used by the LLM to perform AQM for new interactions in the call center.

Abstract: A transaction which targets an object store employing an open table format (OTF) may be detected by a database execution engine. Next, the database execution engine performs a determination step to determine which OTF enhancement levels to apply to the detected transaction. Then, the database execution engine applies one or more OTF enhancement levels to the transaction based on the determination step. Next, the database execution engine causes the transaction to be processed with the applied one or more OTF enhancement levels. Then, the database execution engine returns a result of the transaction processing to a computing device.

Abstract: A host computer is configured to issue one or more unmap commands to a file system of a storage device, the file system being shared by a plurality of host computers including the host computer, by performing the steps of: acquiring unmap privilege information from the storage device, the unmap privilege information indicating whether or not an unmap privilege is available to the host computer; in response to determining that the unmap privilege is available, transmitting a request to update an unmap privilege file stored in the storage device to indicate that the host computer has the unmap privilege; and then issuing to the file system, the one or more unmap commands to deallocate storage space from one or more files of the file system.

Abstract: Systems and methods for event tracking are disclosed. In one aspect, a set of venues is generated. A set of events that have occurred at one or more venues in the set of venues may be generated. One aspect includes querying a user media database associated with a user, and extracting metadata from one or more media files in the user media database. A match between at least a portion of the metadata and one or more events from the set of events may be determined. In an aspect, responsive to the determining, an entry in a matched events database corresponding to the match is created. A list of events attended by the user may be prepared. The list of events may include the matched events.

Abstract: A preferred aggregate store for a multidimensional database receives and stores intermediate data generated as part of a larger query for avoiding repetitive or redundant data retrievals incurring costly data paths. Aggregates include intermediate tables and sets of data, often generated from a join of two or more distinct data tables, combined for generating a query result. In the event an aggregate is called for, certain storage locations may be preferable to others due to network distance, fees for storage and processing, as in the case of cloud storage, or write accessibility. Designation of a preferred aggregate store ensures that aggregates called for by the query processing are stored in a beneficial location for cost and efficiency.

Abstract: Systems, devices, and methods are provided for object oriented versioning and management. Techniques described herein may relate to determining a first event associated with a first binder, wherein the first event encodes a first set of elements, determine a second event associated with a second binder, wherein the second event encodes a second set of elements, and determine a version of a data object by at least: determining a hierarchal relationship between the first binder and the second binder, determining, based at least in part on the first event, a first state, determining, based at least in part on the first state and the second event, a second state, and generating the version of the data object according to the second state. A data object may be a file, object, document, etc.

Abstract: A semantic search system integrates with an AI platform to provide advanced search capabilities by leveraging automatically generated ontologies and knowledge graphs. The system employs natural language processing, machine learning, and large language models to create, update, and align ontologies from diverse data sources. It supports context-aware query interpretation, personalized results, and complex reasoning by incorporating user context, feedback, and domain knowledge. The system optimizes search performance and efficiency through indexing techniques, distributed computing, and continuous learning. With a modular architecture and scalable infrastructure, the semantic search system enables users to retrieve relevant, meaningful, and context-specific information from vast amounts of structured and unstructured data.

Abstract: A method for optimizing a prompt engineering includes graphically presenting a target manipulation interface to a user, wherein different creation modes for the prompt engineering are displayed on the target manipulation interface, and each creation mode supports a structured creation of the prompt engineering, and in response to the user's selection operation of the different creation modes, implementing the structured creation of the prompt engineering with the creation mode selected by the user. The scheme of the present disclosure can provide a solution for optimizing prompt engineering so as to assist users in creating prompt engineering efficiently and with high quality.

Abstract: Aspects of the subject disclosure may include, for example, receiving a user prompt relating to one or more tickets stored in a database, transmitting the user prompt to an LLM to derive a database access query, after the transmitting, obtaining the database access query from the LLM, sending the database access query to a query service to retrieve ticket-related data from the database, based on the sending, obtaining retrieved ticket-related data from the query service, and causing the LLM to generate a response to the user prompt using the retrieved ticket-related data. Other embodiments are disclosed.

Abstract: Embodiments of the present disclosure provides a method and a system for data query. The method may include obtaining a query request; determining a first query condition based on the query request; obtaining a field query result relating to a connection field by querying, based on the first query condition, in a full-text retrieval system, wherein the full-text retrieval system may store one or more indexes; determining a second query condition based on the field query result; and obtaining a target query result by querying, based on the second query condition, in a target type database, wherein the target type database may store one or more target type data tables, and the one or more indexes may be associated with data in the one or more target type data tables via the connection field.

Abstract: A system for assisting a customer is provided. The system includes a database comprising multimedia files, where one or more tags are associated with one or more of the multimedia files. The system further includes a virtual agent server 100 configured to receive input from a first user (customer) and a second user (customer service representative). Further, the virtual agent server 100 processes the received input to understand a context of the input. Subsequently, the virtual agent server 100 identifies one or more multimedia files based on the context and the tags associated with the multimedia files. Subsequently, the virtual agent server 100 shares at least one of the identified multimedia files with at least one of the first user and the second user to enable better understanding between the first user and the second user.

Abstract: A composite AI system and method for advanced reasoning and automation that integrates symbolic knowledge graphs and algorithms with non-symbolic, or connectionist, models such as neural embeddings. A hierarchical architecture enables dynamically distributed, cooperative reasoning through layperson and expert-led challenge-based verification, model blending, model fitness and retraining and selection, comprehensive feedback loops at individual model or model blend or process flow with or without supervision, and specialized routing of processing to account for various operational risk, regulatory, legal, privacy, or economic considerations. Models, datasets, knowledge bases, simulations and simulation components, and embeddings are iteratively refined using knowledge graph elements and model, process, simulation or flow/process optimal hyperparameters which are recorded and tracked. Extraction of symbolic representations from connectionist models links them to curated ontologies of facts and principles.

Abstract: Embodiments of the present disclosure provide a method for book pushing, a method for generating a book recommendation text, an apparatus, and an electronic device. The method for book pushing comprises: obtaining a first book; determining, according to related features of the first book, a target book in at least one second book, the second book and the first book being written by the same author; determining, according to contents of the target book and/or the first book, a recommendation text; generating, according to the recommendation text and related information of the target book, a book recommendation text of the target book; and pushing the book recommendation text to the reader. The method establishes, according to the related features of the first book currently read by the reader, correlations with the target book, and generates the book recommendation text containing the recommendation text.