Systems and methods are directed to providing efficient and fast invocation of concurrent sheet defined functions (SDFs) including dynamic arrays by front-loading the work. At SDF creation time, a SDF cell table, a formula table, and a spill area table are generated. The SDF cell table represents cells from a worksheet that are used for the SDF. The formula table comprises an index of formulas used by the SDF, whereby index identifiers are stored in cells of the SDF cell table. The spill area table comprises an index of spill areas where each dynamic array may automatically spill into. The SDF cell table, formula table, and spill area table are shared between a plurality of invocations of the SDF during invocation time.

A source content routing system is described for distributing source content received from clients such as documents, to translators for performing translation services on the source content. The routing system extracts source content features, which may be represented as vectors. The vectors may be assembled into an input matrix, which may be processed using an artificial neural network, classifier, perceptron, CRF model, and/or the like, to select a translator such as a machine translation system and/or human. The translator provides translation services translation from a source language to a target language, post translation editing, proof reading, quality analysis of a machine, quality analysis of human translation, and/or the like and returns the product to the content routing system or clients.

One embodiment provides a method for generating a digital standard utilizing a trained machine-learning model, the method including: receiving an underlying standard; extracting conceptual units from the underlying standard; classifying, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups; storing the classified extracted conceptual units into a data repository as defined by the schema; displaying, within a user interface on a display of an information handling device, a digital standard in a format based upon the schema; and providing, within the user interface, search and filter functions allowing for finding information related to the digital standard. Other aspects are described and claimed.

In some embodiments, the present disclosure provides for an exemplary computer-implemented system that may include a longitudinal data engine, including: a processor and specialized index generation software to generate: an index data structure for a respective event type associated with each respective subject or object; where each respective index data structure is a respective event type-specific data schema, defining how to store events of a particular event type to form longitudinal data of each respective subject or object; an ontology data structure that is configured to describe one or more properties of a respective event of a respective subject or object; and longitudinal data extraction software to extract a respective longitudinal data for a plurality of index data structures and a plurality of ontology data structures associated with a plurality of subjects or objects.

A repository of graph based visual programming language code instances is analyzed. A similar code portion pattern duplicated is detected among a group of graph based visual programming language code instances included in the repository of graph based visual programming language code instances including by using an index and tokenizing one or more graph nodes connected by one or more graph edges included in a flow corresponding to at least one graph based visual programming language code instance in the group of graph based visual programming language code instances. Within a visual representation of at least one of the group of graph based visual programming language code instances, elements belonging to the detected similar code portion pattern are visually indicated.

The present disclosure provides systems and methods for building an inventory database with automatic labeling. A system can maintain a hierarchical concept tree including labels. Each of the labels is associated with a set of attributes and a respective embedding. The system can receive, from a provider device, a request to generate labels for an item of media content. The request can include a request attribute. The system can generate, using a gated categorical model, document embeddings for the item of media content. The system can select a subset of the labels based on the request attribute. The system can determine a respective label score for each label of the subset of the labels based on the document embeddings and the respective embedding of the label. The system can provide a selected label of the subset of the labels based on the respective label score of the selected label.

A method, system and computer-usable medium are disclosed for using travel-related cognitive graph vectors.

A method, system and computer-usable medium are disclosed for using travel-related cognitive graph vectors.

A system for providing a search service application is disclosed and includes an application builder component that provides a search model for a first object of a plurality of objects. The search model is based at least on an end-user input field corresponding to a first attribute of the first object and a search result output field corresponding to a second attribute of the first object. The search model is also associated with a backend data store that supports a storage structure that stores information relating to the first object. The system also includes a deployment engine that automatically configures a search engine system associated with the backend data store to place a portion of indexed data into a first partition and to place another portion of indexed data into at least another partition based on the search model.

A system for providing a search service application is disclosed and includes an application builder component that provides a search model for a first object of a plurality of objects. The search model is based at least on an end-user input field corresponding to a first attribute of the first object and a search result output field corresponding to a second attribute of the first object. The search model is also associated with a backend data store that supports a storage structure that stores information relating to the first object. The system also includes a deployment engine that automatically configures a search engine system associated with the backend data store to place a portion of indexed data into a first partition and to place another portion of indexed data into at least another partition based on the search model.