The present disclosure provides a method for storing data, including: storing data in a first node, the first node being selected from a first node set including a first edge node and child nodes thereof; selecting, from a second node set including a second edge node and child nodes thereof, a second node for storing the data, the first edge node being a child node of the second edge node; and storing the data in the second node. The present disclosure further provides a method for searching for data. The present disclosure can reduce the time for searching for data in a distributed storage system.

The invention provides a relevance feedback system and computer-implemented method for performing a search in a vector space comprising a first number of target vectors. The method comprises forming a first search query, determining a second number of first search hit vectors among the first number of target vectors based on the first search query vector using a first distance function, determining a third number of flagged vectors, determining a vector subspace spanned by the flagged vectors and/or a second distance function by utilizing the flagged vectors, and determining a plurality of second hit vectors among the target vectors based on the first search query vector and the vector subspace and/or the second distance function.

A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

The present disclosure relates to generating additional insight data for search results. Individual search results may be obtained and used to generate a parse tree for the search result data. A dependency graph may then be generated using the parse tree, where the dependency graph includes a root node that corresponds to a query parameter. A scoring or weighting algorithm is applied to the dependency graph to generate and aggregate scores for nodes in the dependency graph relative to the root node. The generated scores or weights are used to generate insight data for the search results.

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.

A word completion method and apparatus are described. The method is applied to a search scenario and is used to complete an incomplete word entered by a user. The method is based on an improved trie. Hot words are stored in some nodes of the trie. In the word completion method, a target node that matches a character string is searched in the trie, and at least one completed word is output to a user based on a hot word stored in the target node. Word completion efficiency is improved, and a case in which a word is recommended to a user when the user enters an excessively short character string is avoided.

Systems and methods are provided for indexing a document according to identified events. An event-based indexing system includes a source interface configured to receive the document from an associated data source and format the document for processing and an indexer configured to extract event mentions from the document, with a given event mention comprising a verb and at least one of a subject and an object of the verb. A document index is configured to store the extracted event mentions such that a given document from an associated document corpus can be retrieved according to its associated event mentions

A method and system are provided to support automated modification to a multiple node tree structure. Each clause and each logical operator are defined in the tree structure as nodes. In addition, each link emanating from a child node to a parent node is defined as a child link, and each link emanating from a parent node to a child node is defined as a parent link. The selection and location of an operator for placement in the tree structure will be automated in response to the position selected.

A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

A method and an apparatus for providing a safe operation of a technical system including a plurality of system components. The method includes the steps of: a) providing a safety analysis model matured by knowledge about former implementations of the respective system components in different context, b) whereby system components' dependencies are modeled by connecting inports with outports of the respective system components and/or vice versa, c) whereby at least one or a plurality of such in and/or outports are associated with input failure modes and/or output failure modes, d) characterized in automatically uncovering inconsistencies caused by at least one system component to be integrated in connection with at least another system component whereby the input and/or output failure mode of the system component carries the knowledge from another implementation into the context.