An analytics platform for the extraction of structured observations from largely narrative sources using a hybrid approach of user configuration and machine learning is provided. The analytics platform collects and normalizes data from public and private sources and applies extractions to the data to create a world view of objects, traits, and relationships of interest and maintains that world view as data and/or extractions are updated. The platform is further configured to apply queries to the extracted world view for a variety of purposes including scoring objects for prioritized attention, generating notifications when specific conditions are met, providing data sets for exploratory analysis, and triggering the automatic collection of enhancing data from external sources.

Systems, devices, and methods of the present invention create a searchable index that includes informative portions of text. In an example, a computer-implemented method creates a discourse tree from a body of text. For each non-terminal node in the discourse tree, the method identifies a rhetorical relationship associated with the non-terminal node. The method labels each terminal node associated with the non-terminal node as either a nucleus or a satellite. The method further accesses a rule associated with the rhetorical relationship, and selects, based on the rule, selects the fragment associated with the nucleus. The method creates a searchable index including the selected fragments.

Systems and methods are disclosed for parsing logs from arbitrary or unknown systems or applications by capturing heterogeneous logs from the arbitrary or unknown systems or applications; generating one pattern for every unique log message; building a pattern hierarchy tree by grouping patterns based on similarity metrics, and for every group it generates one pattern by combing all constituting patterns of that group; and selecting a set of patterns from the pattern hierarchy tree.

Software code changes are facilitated by receiving as input a user query specifying a search term and automatically generating a ranked list of connected call trees based on the search term. Each connected call tree identifies subroutines that contain an identifier matching at least part of the search term or that are linked to a subroutine that contains an identifier matching at least part of the search term. The ranked list of connected call trees is displayed as a diagram.

Disclosed are systems, computer-readable mediums, and methods for representing text. A document that includes text is received in a first format. A universal text representation of the document is created using a first filter associated with the first format. The universal text representation presents the text and supported non-text data and preserves unsupported data with binding to supported data. The universal text representation is modified based upon input from a user using a program in a what you see is what you get (WYSIWYG) mode. The user can see a location of where the supported data and unsupported data are kept. The modified universal text representation is exported using a second filter associated with a second format. The supported and unsupported non-text data are exported.

A device implementing a system for expanded search includes a processor configured to identify plural words, and generate, for each word of the plural words, a word vector based on a proximity of the word relative to other words of the plural words, the word vector comprising plural dimensions. The processor is further configured to create a compressed word vector structure comprising clusters of subsets of the plural dimensions across the word vectors, each cluster including similar values of the respective dimensions, convert the word vectors to points on at least one plane, and partition the at least one plane into nested groupings of the points based on a threshold number of points per nested grouping. The processor is further configured to create a tree look-up structure of the nested groupings, and provide the compressed word vector structure and the tree look-up structure to a client device.

Systems and methods for generating a fusion score between electronic documents. The method includes receiving a first electronic document by a document management system. The method further includes extracting a first set of features from the first electronic document including at least one feature type indicating the hierarchical structure of the first electronic document. The method also includes receiving a second electronic document by the document management server. The method further includes extracting a second set of features from the second electronic document including at least one feature type indicating the hierarchical structure of the second electronic document. The method further includes generating a fusion score based on a comparison of the first set of features and the second set of features.

With respect to a transforming method for execution by at least one computer, the transforming method includes transforming a first probability distribution on a space defined with respect to a hyperbolic space to a second probability distribution on the hyperbolic space.

A method includes selecting, from a database, messages of a first electronic control (ECU) unit according to a specified datum that the first ECU is programmed to provide via a communications bus, generating a first file of the messages of the first ECU, sorting the messages in the first file according to a hierarchy that includes the specified datum, and outputting a third file describing a comparison of the first file and a second file that includes messages of a second ECU.

The invention provides a method and system for training a machine learning-based patent search or novelty evaluation system. The method comprises providing a plurality of patent documents each having a computer-identifiable claim block and specification block, the specification block including at least part of the description of the patent document. The method also comprises providing a machine learning model and training the machine learning model using a training data set comprising data from said patent documents for forming a trained machine learning model. According to the invention, the training comprises using pairs of claim blocks and specification blocks originating from the same patent document as training cases of said training data set.