A system and methods for leveraging a community of users to collaboratively identify bank or investment account transaction descriptions by providing common, more recognizable description, category and location information used most often by the community. A database may be maintained that is accessible by the customer/user community to view, update and provide understandable descriptions for such cryptic descriptions. The database may be searchable such that a customer/user may search a description to determine or update the source of the transaction.

A method for servicing document search requests. The method includes receiving, by a document management service, a document search query from a requesting user, and injecting, into the document search query, a user access vector. The user access vector specifies, for the requesting user, access control lists that are associated with the requesting user. The method further includes identifying, in a document repository, documents that match the document search query with the injected user access vector. A matching document requires a match of terms in the search query with terms in the matching document, and a match of at least one access control list specified in the matching document and at least one of the access control lists specified in the user access vector.

An apparatus for improved version updates in data deduplication includes a baseline module that stores a baseline referrer link in a first cohort of baseline referrer links pointing to a first location in storage where a baseline version data block is stored. The apparatus includes a signpost module that stores to metadata a signpost that points to an updated referrer link in a second cohort of updated referrer links that points to a second location in the deduplicating storage device where an updated version data block is stored in response to the updated version data block being generated. The apparatus includes a cohort update module that replaces the baseline referrer link with the updated referrer link in response to determining that an additional updated version data block matches the updated version data block pointed to by the signpost. A method and a system implement functions of the apparatus.

A search system performs a federated search across multiple databases and generates a ranked combined list of found genealogical records. The system receives a user query with one or more specified characteristics. The system may determine expanded characteristics derived from the specified characteristics. The system searches the various databases with the characteristics retrieving records according to the characteristics. The system combines the retrieved records and ranks them using a machine learning model. The machine learning model is configured to assign a weight to the records returned from each of the genealogical databases based on the characteristics specified in the user query. The machine learning model may be trained by any combination of one or more of: a Nelder-Mead method, a coordinate ascent method, and a simulated annealing method. The ranked combined results are provided in response to the user query.

Coordinated conveyors in an automated system. In an embodiment, the system comprises transport conveyor(s) and storage conveyors, wherein each storage conveyor comprises a plurality of segments configured to hold at least one item, and a portion that is aligned with a portion of a transport conveyor, such that items are moveable from the storage conveyor to the transport conveyor. Software module(s), executed by a processor, receive an instruction to collect item(s) at a single destination location, and, for each of the item(s), identify a segment on a storage conveyor on which the item is held, control that storage conveyor to align the segment with the transport conveyor, move the item from the segment onto the transport conveyor, control the transport conveyor to align the item with the destination location, and move the item from the transport conveyor to the destination location.

Methods, apparatus and computer program product for generating tiered search index fields based on a divided group-based communication data corpus in a group-based communication platform are described herein. In some embodiments, the system provides for receiving a group-based communication data corpus, generating a retrieval score, and assigning each group-based communication data object associated with a retrieval score. Each group-based communication data object may meet or exceed a retrieval score threshold of a high retrieval probability corpus. Each group-based communication data object associated with a retrieval score below the retrieval score threshold may be assigned to a low retrieval probability corpus. High and a low retrieval probability search index fields may be generated and associated with the high and low retrieval probability corpus.

Technology is disclosed herein for enhanced similarity search. In an implementation, a search environment includes one or more computing hardware, software, and/or firmware components in support of enhanced similarity search. The one or more components identify a modality for a similarity search with respect to a query object. The components generate an embedding for the query object based on the modality and based on connections between the query object and neighboring nodes in a graph. The embedding for the query object provides the basis for the search for similar objects.

Various methods, systems, apparatuses, and media for implementing a machine learning model execution module are provided. A processor accesses human resource (HR) attributes and profile information data of users from a database. The processor applies hierarchical clustering algorithm to create a machine learning model by clustering users based on accesses to applications that the users have corresponding to the profile information data of the users. All users in one cluster have the most similar accesses to applications. The processor iterates the process of accessing the HR attributes and the profile information data of the users from the database until it is determined that an optimal number of clusters have been created for the machine learning model.

In predictive natural disaster response, a server determines an affected location predicted to be affected by a natural disaster and determines whether the type of natural disaster requires relocation of an animal population at the affected location. When relocation is required, using machine learning models, the server generates a rehabilitation needs prediction for the relocation, determines an optimal location for the relocation from candidate locations, and generates a relocation plan to relocate the animal population from the affected location to the optimal location. When relocation is not required, using the machine learning models, the server generates a demands prediction for products and services at the affected location, generates a supply prediction for the products and the services at the affect location, and generates a supply plan using the demands and supply predictions.

Multiple stage filtering may be implemented for natural language query processing pipelines. Natural language queries may be received at a natural language query processing system and processed through a query language processing pipeline. The query language processing pipeline may filter candidate linkages for a natural language query before performing further filtering of the candidate linkages in the natural language query processing pipeline as part of generating an intermediate representation used to execute the natural language query.