Abstract: In an example embodiment, a solution for matching entities in a query table with one or more entities in a target table, in the presence of a constraint on the value sum of the matching targets (hereinafter called the “value constraint”), using machine learning techniques, is provided. Specifically, a non-linear objective function is converted to a linear objective function and a machine learning model is trained using the linear objective function, allowing for the use of solver functions from libraries in order to speed matching over existing methods.

Abstract: A method includes receiving a domain search query from a first user, generating a prompt based on the query to instruct a first model to provide a domain recommendation, where the first model is trained by utilizing a dataset including: first data reflecting interactions of users with domain portfolios, second data reflecting domain-related actions performed by the users, third data reflecting behaviors of a second user during a current domain search session, fourth data reflecting behaviors of the second user over a predetermined period covering multiple search sessions, and fifth data reflecting search scenarios of multiple users, determining the domain recommendation against a predetermined rule to form a sanitized domain recommendation, verifying an availability to register the sanitized domain recommendation to form an available domain recommendation, adding industry information to the available domain recommendation to form an enriched domain recommendation, and transmitting the enriched domain recommen

Abstract: Methods and systems described in this disclosure are directed to electronically generating narratives and tracking a user's actions in responses to receiving the narratives. The disclosed system can rank narratives for effectiveness of a narrative based on the responses. In some embodiments, the narratives can be classified into categories based on criteria pertaining to user population data or user-specific data.

Abstract: The present disclosure relates to maintaining extracted data in a group node profile from electronic activities. A group node profile associated with a group entity is maintained. A first data point including an electronic activity or a record object is accessed. The first data point is parsed using a value detection policy to obtain a first value. The group node profile is updated based on the first value. An association score between the group node profile and the first value is generated. A second data point is accessed. The second data point is parsed. The association score between the group node profile and the first value is updated.

Abstract: Systems and methods herein describe embodiments for handling a data drift. An example system accesses the data pipeline, which is comprised of a plurality of stages. For each stage of the plurality of stages in the data pipeline, the system identifies stage schema fields for processing data in the data pipeline and generates a set of stage schema fields comprising the identified stage schema fields in the stage. In response to detecting an origin stage, the system generates a set of pipeline schema fields, whereby the set of pipeline schema fields comprise a union of the generated sets of stage schema fields. The set of pipeline schema fields are then stored.

Abstract: Disclosed is a system to provide information associated with a user device from a server to the user device without disclosing the association to the server. Data structures, created at the server, contain information such as information about restaurants, mechanics, medical conditions, etc. The server creates bundles including two or more data structures containing disparate information, and a unique identifier for each bundle. The server creates a table of contents indicating the unique identifier of a bundle and the information contained in the bundle and sends the table of contents to the device. The server receives the unique identifier of the bundle and provides the bundle having the unique identifier to the device. While the bundle contains the information associated with the user device, because the bundle contains disparate information. the server does not know which information is associated with the user device.

Abstract: A method for labeling data items includes receiving, from a client, user input generated by a user of the client. The method also includes generating query conditions based on the user input. Further, the method includes retrieving, from a custom knowledge system integration module and using the query conditions, a list of label candidates. In addition, the method includes determining, via the client, that the user approves the list of label candidates. Moreover, the method includes generating, based on the determination, a label candidate query using at least the list of label candidates. Further, the method includes submitting the label candidate query to a large language model (LLM) engine. Moreover, the method includes obtaining, in response to the label candidate query, a list of target labels from the LLM engine. Also, the method includes labeling a plurality of unlabeled data items using the list of target labels.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and projection datasets. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The projection datasets are indexes of the canonical dataset and/or the buffer that may have single or multiple column sort-orders and/or particular data formats. The writes to the canonical dataset, projection datasets, and buffer may be asynchronous and therefore the database system is advantageously less resource constrained.

Abstract: Class definitions for an ontology of a domain are determined using a materialized instance graph, where the ontology is used for semantic query execution, automated analytical reasoning, or for machine learning. A plurality of instances graphs for a respective plurality of domain instances are received. A materialized instance graph is generated from the plurality of instance graphs. One or more communities represented in the materialized instance graph are determined. Properties associated with respective communities of the one or more communities are determined. Class definitions are generated, where a class corresponds to a community of the one or more communities and at least a portion of properties associated with the community. Class definitions are assigned to the ontology for the domain.

Abstract: A methods, systems, and devices for secure linking and matching of data elements across independent data systems of a first and a second enterprise are disclosed. The system includes a first private data system having a first private database that may include all attributes known to the first enterprise A reference data system having a reference database and is also part of the first enterprise. The reference database may contain a plurality of identity data records that only contain identity attributes that are used for resolving and verifying identities of unknown data records that are external to the reference data system. A first set of query attributes may be used determine whether a subject represented by the first set of query attributes associates uniquely with a subject of any private data record stored in the first private database. A similar comparison may be made in the reference database.

Abstract: A data processing system performs data processing of raw or preprocessed data. In some embodiments, the data processing system includes a connectivity overlay engine comprising a data ingester, a connectivity generator, an event access control system, and a feature vector generation framework.

Abstract: Systems and methods of tracking utilization of tableware are presented. In one exemplary embodiment, a method of maintaining a historical record of food allergen exposure to tableware is performed by an electronic device having a sensing device operable to sense an identifier specific to and disposed with tableware. The tableware identifier is specific to a cryptographic digital asset stored on the blockchain as a code that represents the tableware identifier. Further, the cryptographic digital asset includes a reference to information that represents a historical record of any food allergen exposure to the tableware. The tableware identifier code and the food allergen exposure information reference are included with the cryptographic digital asset. The method includes sending, to the blockchain, an indication that includes a request for block data associated with the cryptographic digital asset based on the tableware Identifier disposed on the tableware that is sensed by the sensing device.

Abstract: Systems and methods include reception of a first request to copy a database to a second tenant. In response to the first request, first metadata associating the second tenant with a first shard and a second shard of a database table is generated. A second request to access the first shard is received from a requestor associated with the second tenant and, in response to the second request, it is determined that the first shard is not stored in any of a plurality of storage nodes of a storage layer. In response to the determination, an instruction is issued to recover the first shard to a first storage node from a first backup location, and an identifier of the first storage node is returned to the requestor.

Abstract: Systems and methods are for improving latency and throughput for metadata-heavy workloads and/or workloads including metadata bursts by decoupling data journal records and metadata-only journal records are provided. According to one embodiment, expedited and independent space reclamation is facilitated by differentiating between various types of journal records chains of which should be retained until different conditions are met. For example, data journal records may be added to data journal record chains within a persistent KV store and metadata-only journal records may be added to metadata-only journal record chains within the persistent KV store. Reclamation of spaced utilized by a data journal record chain may be reclaimed after both remote node data flush has been completed and the completion of a local CP for all records in the chain, whereas records of a metadata-only journal chain may be freed independently upon completion of a local CP for all records.

Abstract: An online concierge system generates a graph connecting items with attributes of the items and other items. Hence, the graph includes nodes corresponding to attributes and nodes corresponding to items, with an item connected to attributes of the item in the graph. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and compares different combinations of terms to the graph to determine connections between different combinations of terms in the graph. Based on measures of connectedness between combinations of terms and connections in the graph, items are identified from one or more combinations of terms. Information about the identified items is presented to the customer.

Abstract: A numerical time series analysis and data simplification system and a software-implemented numerical time series analysis and data simplification process are disclosed. The numerical time series analysis and data simplification system and process provide several functions including channel math, signal filtering, and concatenation functions. The numerical time series analysis and data simplification system and process focus on a very specific engineering problem space and provide a generic solution to the likely variations of the problem space.

Abstract: A system and method are provided for processing hierarchical data. The method includes receiving a first set of data from a plurality of sources, each source providing data records for entities in an organizational hierarchy processing the first set of data to generate a preliminary data file for the entities by combining the data records to populate fields in the data file and receiving a second set of data from at least one additional source, each additional source providing additional data records for the entities. A hierarchical connectivity platform may use machine learning to analyze the data. The second set of data is processed to update missing fields in the preliminary data file, for the entities, to generate an output data file comprising a list of the entities in the hierarchy with the associated data fields for each entity; and providing the output data file to a platform.

Abstract: Systems and methods for controlling admission of transactional operations for execution are provided. An admission queue configured to control admission to an LSM tree can receive a plurality of work items corresponding to a plurality of tuples. The plurality of work items can be queued in the admission queue for execution based on the plurality of tuples. Indications of a capacity of the LSM tree and a size of each work item of the plurality of work items can be determined. A plurality of tokens configured to enable admission of the plurality of work items to the LSM tree can be generated based on the indications of the capacity of the LSM tree and the size of each work item. Based on the plurality of tokens, a work item of the plurality of work items can be admitted from the admission queue to the LSM tree.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: An electronic device suggests contacts and calendar events for users based on their messages. The device can analyze a user's messages for contact and event information and automatically generate or update suggested contacts and calendar events for the user based on this information. The suggested contacts and calendar events can be searchable as if they were manually entered by the user, and the user can choose to add or ignore the suggested contacts and calendar events.