Abstract: Systems and methods for dynamically generating object models corresponding to regulations. According to certain aspects, a server computer may access a regulation and automatically generate a summary of the regulation based on a specific set of sentences. The server computer may additionally determine a set of topics and named-entity attributes for text within a regulation object model, as well as a probability that a topic or attribute is applicable to the regulation. Further, the server computer may generate and enrich object models according to the various analyses and avail the enriched object models for review by entities and users of regulatory compliance services.

Abstract: Systems and methods for dynamically generating object models corresponding to regulations. According to certain aspects, a server computer may access a regulation and automatically generate a summary of the regulation based on a specific set of sentences. The server computer may additionally determine a set of topics and named-entity attributes for text within a regulation object model, as well as a probability that a topic or attribute is applicable to the regulation. Further, the server computer may generate and enrich object models according to the various analyses and avail the enriched object models for review by entities and users of regulatory compliance services.

Abstract: Systems and methods for dynamically generating object models corresponding to regulations. According to certain aspects, a server computer may access a regulation and automatically generate a summary of the regulation based on a specific set of sentences. The server computer may additionally determine a set of topics and named-entity attributes for text within a regulation object model, as well as a probability that a topic or attribute is applicable to the regulation. Further, the server computer may generate and enrich object models according to the various analyses and avail the enriched object models for review by entities and users of regulatory compliance services.

Abstract: Enhanced spelling correction is provided. An enhanced spelling correction service may determine any misspellings (e.g., a word of the text containing an identified spelling error) in text using lexicon-based spelling correction. Each misspelling is assigned an error flag. The service can communicate each misspelling to a language model-based spell checker and receive, for each misspelling, an error confidence signal from the language model-based spell checker. For each misspelling having an error confidence signal indicating a low confidence that the identified spelling error is an actual spelling error, the service can determine whether to maintain or suppress the error flag by applying decision logic. In response to determining to maintain the error flag, the service can surface a visual indication of the spelling error. In response to determining to suppress the error flag, the service can suppress the error flag whereby the visual indication of the spelling error is not surfaced.

Abstract: A “Linguistic Complexity Tool” uses Machine Learning (ML) based techniques to predict “source complexity scores” for localization of source language assets or resources (i.e., “source content”), or subsections of that content, to provide users with predicted levels of difficulty in localizing source content into target languages, dialects, or linguistic styles. These predicted source complexity scores provide a number of advantages, including but not limited to, improved user efficiency and user interaction performance by identifying source content, or subsections of that content, that are likely to be difficult or time consuming for users to localize. Further, these source complexity scores enable users to modify source content prior to localization to provide lower source complexity scores, thereby reducing error rates with respect to localized text or language presented in software applications or other media including, but not limited to, spoken or written localizations of the source content.