Methods and systems are provided for searching information in a distributed data processing system. A system for processing a semantic search query where the system may include a memory and a processor coupled to the memory being configured to, receive a structured search query, process the structured search query to deconstruct into query elements, identify a set of connected elements that define a data source associated with the received structured search query based on a processed query element, process the query elements to determine one or more command data element types associated with the received structured search query, and process data associated with the defined data source according to a command data element type to develop a semantic search query resultant data set.

Methods for providing enhanced services to users participating in communication sessions (CS), via a virtual assistant, are disclosed. One method receives content that is exchanged by users participating in the CS. The content includes natural language expressions that encode a conversation carried out by users. The method determines content features based on natural language models. The content features indicate intended semantics of the natural language expressions. The method determines a relevance of the content and identifies portions of the content that are likely relevant to the user. Determining the relevance is based on the content features, a context of the CS, a user-interest model, and a content-relevance model of the natural language models. Identifying the likely relevant content is based on the determined relevance of the content and a relevance threshold. A summary of the CS is automatically generated from summarized versions of the likely relevant portions of the content.

A virtual file organization system, method and program product are disclosed. Included is a system that assigns classification tags to files stored within a storage system based on a natural language processing (NLP) context analysis of each file; and a virtual smart folder that is viewable within a user interface, wherein: opening the virtual smart folder causes a set of virtual subfolders to be displayed in which each virtual subfolder includes a category title; opening of a virtual subfolder causes a set of files residing at disparate locations in the storage system to be displayed; and the files displayed by opening the virtual subfolder each include an assigned classification tag that is associated with the category title of the virtual subfolder.

A method for rendering context based information on a user interface includes receiving a user request to extract the context based information from a database. The database includes a plurality of documents and the request includes at least one search criteria required to determine a context of the user request. The method includes generating a list of documents corresponding to the context of the user request and rendering on a viewing portion of the user interface the list of documents corresponding to the context of the user request.

Techniques are disclosed relating to methods that include preprocessing, by a computer system, records of a database to create one or more token sets for a given record. The created token sets may correspond to ones of a plurality of search string functions, and may include token sets that include a plurality of possible substrings located within data strings of a corresponding database record. The methods may further include receiving a query for a search of the database. The query may include at least one of the plurality of search string functions. The method may also include performing the search by traversing, using at least a portion of the records, at least one token set corresponding to the included search string functions, as well as returning results for the search based on the query and the traversing.

A safety case discovery system includes a scenario framework and safety protocols for edge cases. The safety case discovery system receives sensor data generated by at least one sensor during operation of a vehicle and stores the sensor data in a data warehouse. The data warehouse can be queried based on a predefined scenario description to produce a subset of records which are ranked based on a relevancy of the records to the predefined scenario description. The safety case discovery system deduplicates the ranked results to produce edge cases and updates the safety framework. The safety case discovery system can train a machine learning model vehicle based on the edge cases.

Methods and system for item matching are described. In one embodiment, compatibility-based text for an item may be accessed. A compatibility identifier may be identified based on the compatibility-based text. The compatibility identifier may be associated with an item cluster. The compatibility identifier may be used to identify a plurality of matching items. A result may be provided based on identification of the plurality of matching items. Additional methods and systems are disclosed.

Systems and methods are presented herein for recording portions of a media asset relevant to recording criteria. A media application receives input indicating the recording criteria and identifying a first keyword. The media application accesses a data structure to identify a first node associated with the first keyword. The data structure includes the first node and a plurality of nodes connected to the first node via a plurality of paths. The media application receiving audio component data for a portion of the media asset extracts a term from the audio component data, and identifies a second node in the data structure that is associated with the extracted term. The media application calculates a path score for the portion of the media asset based on a path size in the data structure between the first node and the second node. When the score is high enough, the portion of the media asset is recorded.

Systems and methods are described herein for interpreting natural language search queries that account for contextual relevance of words of the search query that would ordinarily not be processed, including, for example, processing each word of the query. Each term or phrase is associated with a respective part of speech, and a frequency of occurrence of a combination of adjacent terms or phrases public domain is determined. A relevance of each term is then determined based on its respective type of term and frequency of occurrence in the public domain. The natural language search query is then interpreted based on the importance or relevance of each term.

From a set of natural language text documents, a concept tree is constructed. For a node in the concept tree a polarity of the subset represented by the node is scored. A second set of natural language text documents is added to the subset, the adding resulting in a modified subset of natural language text documents having a polarity score within a predefined neutral polarity score range. From the modified subset, a bin of sentences is selected according to a sentence selection parameter, a sentence in the bin of sentences being extracted from a selected document in the modified subset. A sentence having a factuality score below a threshold factuality score is removed from the bin of sentences. From the filtered bin of sentences a new natural language text document corresponding to the filtered bin of sentences is generated using a transformer deep learning narration generation model.