A key value (KV) store, a method thereof, and a storage system are provided herein. The KV store may include a key logger; and a processor configured to receive a first command for storing a first KV in the KV store, write a first value of the first KV to a first NAND page, generate an extent map for identifying the first memory page including the first value, write the extent map to a second memory page, append an entry for storing the first KV to the key logger, and update a device hashmap of the KV store to include a first key of the first KV, upon a threshold being met within the key logger.

A method for maintaining links is described. A document selection is received, including a first destination document containing a first link to linked content. A first source document containing the linked content and not contained within the document selection is identified using the first link. A copy mode is selected, using an intrinsic property associated with the first link, from: a first mode where a second destination document that is a copy of the first destination document is generated and includes a second link to the linked content within the first source document, without copying the first source document, and a second copy mode where i) a second source document that is a copy of the first source document is generated, ii) the second destination document is generated and includes a second link to the linked content within the second source document. The selected copy mode is performed.

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.

Systems, devices, and methods of the present invention calculate a rhetorical relationship between one or more sentences. In an example, a computer-implemented method accesses a sentence comprising a plurality of fragments. At least one fragment includes a verb and a words. Each word includes a role of the words within the fragment. Each fragment is an elementary discourse unit. The method generates a discourse tree that represents rhetorical relationships between the sentence fragments. The discourse tree includes nodes including nonterminal and terminal nodes, each nonterminal node representing a rhetorical relationship between two of the sentence fragments, and each terminal node of the nodes of the discourse tree is associated with one of the sentence fragments. The method matches each fragment that has a verb to a verb signature, thereby creating communicative discourse tree.

Systems, devices, and methods of the present invention detect rhetoric agreement between texts. In an example, a rhetoric agreement application accesses a multi-part initial query and generates a question communicative discourse tree that represents rhetorical relationships between fragments of the query. The application identifies a sub-discourse tree from the question communicative discourse tree. The application generates a candidate answer communicative discourse tree for each candidate answer of a set of candidate answers. The application computes a level of complementarity between the sub-discourse tree and each candidate answer discourse tree by applying a classification model to the sub-discourse tree and candidate answer communicative discourse trees. The application selects an answer from the candidate answers based on the computed complementarity, thereby building a dialogue structure of an interactive session.

Generating textual entailment pair by a natural language processing (NLP) system. The NLP system receives two input texts, such as a question and a candidate answer. The NLP system queries a database and retrieves passages likely to include text that support the candidate answer. The NLP system generates parse trees and performs term matching on the passages and scores them according to the matching. The NLP system detects anchor pairs in the question and in the passage and aligns subgraphs (within the parse trees) of one to the other based on matching. The NLP system identifies aligned terms in the question and the passage that are not in the aligned subgraphs. The NLP system identifies text fragments, for the question and the passage, within the non-aligned segments of their respective parse trees, that connect the aligned term to the aligned portion of the subgraph.

Metadata of a storage object is managed. An example method for managing metadata of a storage object comprises: in response to receiving a request to access metadata of a storage object, obtaining a first identifier of the storage object from the request; determining, based on the first identifier, a second identifier of a page where the metadata is located, an address of the page and the second identifier being stored in association in an entry of a page table distributed among a plurality of storage devices with different access speeds; determining, from the plurality of storage devices, a storage device storing the entry; and obtaining the address of the page by accessing the entry from the storage device, so as to access the metadata from the page.

An illustrative embodiment includes a method for analyzing unstructured multidimensional data with a neural network. The method includes designing the neural network at least in part by defining differential operators conforming with dimensions of the data. The method also includes performing forward propagation at a given convolution layer of the neural network at least in part by: obtaining one or more convolved values at least in part by performing convolution over an object within the data, processing respective convolved values to obtain output, and updating the object based at least in part on the output.

Disclosed are a log parsing method and device, a server and a storage medium, relating to the field of network operation and maintenance. The method includes: acquiring (101) sample log data; performing (102) clustering processing on the sample log data according to the length of each sample log in the sample log data, and beginning and ending keywords of each sample log in the sample log data, to obtain a plurality of log clusters; determining (103) a quality score of each log cluster of the plurality of log clusters obtained by the clustering processing; and parsing (104) a log according to the plurality of log clusters and quality scores of the plurality of log clusters.

A system, server device, and method are provided for managing document metadata. The method includes storing metadata in a graph separately from documents with which the metadata is associated and connecting metadata in the graph according to a hierarchy, with each node of the graph being classified based on metadata content. The method also includes assigning properties to edges in the graph connecting the nodes; receiving, via a communications module, an instruction to update the metadata; and dynamically updating at least one edge or node in the graph according to the instruction without requiring access to an associated document. The method also includes receiving, via the communications module, an inquiry related to a document; and responding to the inquiry, via the communications module, after accessing metadata associated with the document by navigating the graph.