Techniques for dynamically generating user interface (UI) components based on hierarchical component factories are disclosed. In one example, a component factory corresponding to each of a plurality of UI components may be defined. The plurality of UI components associated with an application may be registered with a common registry using associated metadata and configuration information. Each UI component may be mapped to a component factory of an associated parent UI component based on the associated metadata. A request to render at least a portion of the application on a UI may be received. At least one UI component corresponding to the request at each level in a hierarchy may be generated, at runtime, using the component factory associated with the at least one UI component and the common registry. The at least one generated UI component may be rendered on the UI.

Described herein is a regulatory parser that downloads and efficiently processes regulatory documents. The regulatory documents may be from different sources and may have different formats. The regulatory parser parses all of the text in the regulatory documents and converts into a predetermined, single format for downstream applications. The text is organized and stored in a structured tree, organized into one or more hierarchies with nodes storing segments of text from a regulatory document. In some embodiments, each node in the regulatory tree may represent a segment of text. Partitioning the text of a regulatory document into segments of text may make the storage and querying of the regulatory documents more manageable. The organization and structure of the structured tree may reduce the times and resources needed for accessing and searching for a regulatory citation. The structured tree may allow a user to manipulate a regulatory document or text.

Systems, methods, and storage media for extracting patent document templates from a patent corpus are disclosed. Exemplary implementations may: obtain a patent corpus; receive one or more parameters; determine one or more subsets of the patent corpus by filtering the patent corpus based on the one or more parameters; identify one or more document clusters within individual ones of the one or more subsets of the patent corpus; obtain a patent document template corresponding to the first document cluster; and/or perform other operations.

Systems, methods, and storage media for extracting patent document templates from a patent corpus are disclosed. Exemplary implementations may: obtain a patent corpus; receive one or more parameters; determine one or more subsets of the patent corpus by filtering the patent corpus based on the one or more parameters; identify one or more document clusters within individual ones of the one or more subsets of the patent corpus; obtain a patent document template corresponding to the first document cluster; and/or perform other operations.

Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving, at a local device from a remote device, query data representative of a question relating to source content of a source document, and determining whether one or more pre-determined questions stored in a question-answer cache maintained at the local device matches the query data according to one or more matching criteria. The method further includes obtaining from the question-answer cache, in response to a determination that at least one of the pre-determined questions matches the query data received from the remote device, at least one answer data item, associated with at least one pre-determined question, corresponding to an answer to the question relating to the source content.

Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving, at a local device from a remote device, query data representative of a question relating to source content of a source document, and determining whether one or more pre-determined questions stored in a question-answer cache maintained at the local device matches the query data according to one or more matching criteria. The method further includes obtaining from the question-answer cache, in response to a determination that at least one of the pre-determined questions matches the query data received from the remote device, at least one answer data item, associated with at least one pre-determined question, corresponding to an answer to the question relating to the source content.

A scenario generation apparatus includes: a keyword selection unit that extracts a hierarchical structure from documents that is a basis of a scenarios for use in chatbot and has the hierarchical structure, and selects keywords from the headings in each layer of the extracted hierarchical structure, a link candidate generation unit that generates a first scenario candidate in which a link is set between the keywords and a second scenario candidate in which a link is not set between the keywords, by using documents, an evaluation value calculation unit that calculates an evaluation value for the link for each of the generated first scenario candidate and the second scenario candidate according to a setting rule, and a scenario generation unit that adopts one of the scenario candidates based on the calculated evaluation value and generates the scenario using the adopted scenario candidate.

A scenario generation apparatus includes: a keyword selection unit that extracts a hierarchical structure from documents that is a basis of a scenarios for use in chatbot and has the hierarchical structure, and selects keywords from the headings in each layer of the extracted hierarchical structure, a link candidate generation unit that generates a first scenario candidate in which a link is set between the keywords and a second scenario candidate in which a link is not set between the keywords, by using documents, an evaluation value calculation unit that calculates an evaluation value for the link for each of the generated first scenario candidate and the second scenario candidate according to a setting rule, and a scenario generation unit that adopts one of the scenario candidates based on the calculated evaluation value and generates the scenario using the adopted scenario candidate.

A solution for spreadsheet table transformation is provided. In this solution, one or more header areas and a data area of a spreadsheet table are detected. A hierarchical structure of each of the header areas is determined by analysis of cell merging and/or indents in the header area, and/or a function relationship between data items in corresponding cells of the data area. The spreadsheet table can be transformed to a relational table based on recognition of the hierarchical structure of the header area. In this way, by facilitating understanding of header structures based on the header hierarchy, it is possible to achieve automated transformation from spreadsheet tables to relational tables.

Techniques include obtaining, with a computer system, a natural-language-text document comprising unstructured text; generating, with the computer system, based on a first set of machine learning model parameters, a neural representation of the unstructured text; identifying, with the computer system, based on the neural representation, a trigger word located within the unstructured text and associated with a first category; determining, with the computer system, based on the trigger word, a region within the unstructured text comprising descriptors associated with the first category; determining, with the computer system, from the region based on a second set of machine learning model parameters, a descriptor describing an action or condition of the first category; generating, with the computer system, a data model object comprising the descriptor defining an action or condition of the first category; and storing, with the computer system, the data model object in memory.