147 results about "Alias" patented technology

A distributed indexing and resolution architecture is disclosed for decentralized systems requiring modular, trust-scoped mutation control and dynamic alias governance. The system comprises a plurality of index entries arranged in a parent-child hierarchy, each associated with a structured alias and governed by one or more anchor nodes. Anchors perform localized resolution, mutation validation, and restructuring operations under deterministic policy constraints, enabling semantic scope enforcement and entropy-sensitive adaptation without requiring global consensus or centralized control. The architecture supports scoped alias traversal, asynchronous mutation proposals, and elastic anchor registration based on system state metrics. The indexing substrate may be integrated into heterogeneous infrastructures, including systems comprising distributed software agents, semantic execution platforms, or pseudonymous identity frameworks. Anchors coordinate within defined trust domains to ensure lineage continuity, dynamic rekeying, and semantic integrity across independently governed segments of a decentralized namespace.

The invention discloses a false information multi-source association reasoning system based on a knowledge graph, and the system comprises a data collection and standardization module which is used for carrying out the multi-source collection and duplicate removal of a text, and generating a structured input data set; the semantic extraction and normalization module is used for executing alias merging and disambiguation and outputting a semantic extraction result; the entity alignment module is used for cross-platform entity matching and confidence evaluation, entity identification unification and attribute and alias merging; the graph construction and anchor point module is used for constructing a fact graph and a traceability graph; the candidate constraint generation module is used for forming a candidate constraint set based on the multi-source evidence statistics support degree; the space-time constraint and weight reduction module is used for executing path consistency and joint constraint according to Allen and RCC8 to obtain an updated evidence weight result; and the evidence chain and pushing module is used for enumerating and scoring the evidence chain and pushing the evidence chain through an external interface. According to the invention, false information multi-source association reasoning is realized.

A software package is received and unpacked into multiple components comprising plural functions. Each function is lifted from machine code into static single-assignment intermediate representation and tokenized to produce semantics-preserving embeddings. Intermediate-representation data-flow features are extracted, including detection of constant static variables on a stack, stack reaching definitions, uninitialized variables, and intra-procedural aliases. For each component, the embeddings and features are input to a machine-learning model trained on semantic properties derived from a corpus of software packages to generate a software supply chain risk level. Data characterizing the risk level is provided to a consuming application. When the risk level satisfies a remediation criterion, a remediation action is initiated, including generation of a source-code patch recommendation for an identified root-cause function, insertion of a runtime guard into the component, or issuance of a security advisory for distribution to a security operations dashboard.

The invention belongs to the technical field of natural language processing and geographic information systems, and particularly relates to a region address standardization method based on knowledge graph enhanced retrieval. Cleaning and preprocessing the original address text input by the user; utilizing a fine-tuned large language model to identify a geographic entity and performing standardized expansion on variant expression to generate a query candidate set; entity linking and context retrieval are carried out based on the knowledge graph, and attributes, hierarchy and spatial topology information of associated entities are obtained; in combination with the original input and the map context, an enhanced retrieval query text is generated through large language model reconstruction; vectorized semantic retrieval is carried out through the fine-tuned embedding model, and a preliminary candidate address set is obtained; carrying out multi-dimensional refined sorting by adopting a resorting model; and generating a structured standard address by using a large language model, and outputting the structured standard address after multi-level verification. According to the method, the problems of ambiguity resolution, alias recognition and context understanding in address processing are solved, and the accuracy and robustness of address standardization are improved.

The invention belongs to the related technical field of graph calculation and streaming data processing, and particularly relates to a streaming graph-oriented random walk acceleration method, which comprises the following steps of: storing vertex information by adopting a hierarchical graph storage architecture consisting of a base layer, a dynamic extension layer and a chain storage layer, enabling neighbor ID (Identity) intervals stored in each layer to be different, and according to the degree change of a target vertex, carrying out random walk acceleration on the target vertex; dispersing and storing neighbors in different layers through a cross-layer migration mechanism; dividing neighbor information of the target vertex into a plurality of independent partitions, and independently constructing an alias table for each partition; a DPST is constructed for each target vertex, and one node maintains one partition to accumulate and add all neighbor weight values; when the neighbor weight of the target vertex changes, modifying the alias table of the changed partition, and updating the DPST; resampling is started from the position where the target vertex appears for the first time in all the migration sequences, and a sampling mode is selected according to the size relation between the weight skew factor of the target vertex and the threshold value. According to the invention, the random walk speed can be improved.

The invention belongs to the technical field of industrial data processing, and provides an intelligent material matching method and system fusing multi-modal features and fuzzy matching, and the technical scheme is that data in obtained electronic component list data is analyzed, key characters in character strings are identified, and a constructed mapping table is called to carry out mapping replacement on the key characters, so that the matching accuracy of the electronic component list data is improved. Obtaining each field parameter of the mapped electronic component; performing matching based on the constructed manufacturer alias knowledge graph and the mapped manufacturer field parameters to obtain a manufacturer matching result; screening the mapped material number parameters to obtain a material number candidate set, performing semantic similarity calculation based on the material number candidate set and a constructed special word vector model in the field of electronic components, when the similarity is greater than a set threshold, performing accurate matching, otherwise, triggering fuzzy matching, calculating a service score according to a matching result, and obtaining a service result; and performing multi-objective optimization based on a service score result to obtain an optimal matching scheme. And the matching accuracy and the purchasing decision-making efficiency are obviously improved.

Methods, non-transitory computer readable media, and a data server that assist with enabling conversational access to tabular data includes determining in response to a user input, tabular data comprising a header row with header data in each column and one or more table data rows with row data in each column. A first prompt is provided to a large language model to generate a dummy table comprising the header row and a dummy row with dummy row data in each column and a dummy table is received. An alias table comprising the header row and an alias row with alias row data in each column is generated. A second prompt is provided to the large language model to generate a dummy row text representation of the dummy row data, wherein the dummy row text representation includes the alias row data inserted as placeholders of the dummy row data and the dummy row text representation is received. A row text representation is generated for each of the one or more table data rows by replacing the alias row data in the dummy row text representation with row data of corresponding ones of the one or more table data rows.

The invention relates to the technical field of information retrieval, and discloses a term standardization query method and system based on a large language model, and the method comprises the steps: receiving original query, dialogue history and multi-modal input; analyzing the multi-modal input to generate an extended context; candidate aliases are extracted through natural language processing, and a domain term knowledge base is inquired in combination with a term list; adjusting the priority weight according to the user role and the real-time context; constructing a structured prompt including dialogue history, original query, extended context, candidate schemes and task instructions, and inputting a large language model to generate a replacement decision; updating the knowledge base based on user interaction data and model feedback; historical query records are stored to assist in follow-up reasoning. According to the invention, the picture, the PDF and the voice input are analyzed through the multi-modal context enhancement module, the extended context containing the term list and the semantic clue is generated, comprehensive context support is provided for term standardization, and query processing is ensured to adapt to various enterprise scenes.

The invention discloses a zero-sample multi-modal relation extraction method based on a multi-modal large model, which comprises the following steps of: constructing prototype information containing tag names, descriptions and aliases for seen and unseen relation categories, and encoding and aggregating the prototype information into prototype vectors; extracting feature representation of a training sample through a multi-modal large model, and performing fine adjustment on the model by updating low-rank adapter parameters based on the feature representation and a known category prototype vector; and for the input containing the unseen category, extracting the features of the input by using the fine-tuned model, and completing relation identification in combination with the prototype vector of the unseen category. According to the method, the structured prototype knowledge is injected into the low-rank fine tuning process, so that the model keeps semantic perception of the unseen relationship while absorbing the domain knowledge, the relationship extraction accuracy and generalization ability in a zero sample scene are remarkably improved, and the data annotation cost is effectively reduced.

A method is disclosed. The method includes receiving, by a server computer from a user device comprising a transfer application via a communications network, contact data for a plurality of potential users on the user device. The method also includes searching, by the server computer a database, for a set of aliases associated with the potential users in the contact data. The method also includes providing, by the server computer via the communications network, the set of aliases to the user device. The user device is programmed to store the set of aliases in the transfer application, receive a selection of an alias associated with a user, and initiate an interaction with the alias using the transfer application.

Conflicting aliases in database queries are identified with a graph-based approach. A conflict detector builds a base graph comprising nodes representing the database's tables and fields and edges representing relationships between the tables and fields. The detector iterates over one or more database queries and augments the base graph with nodes representing aliases of tables / fields identified in each database query. The detector inserts an edge between each node corresponding to an alias and the node of the base graph corresponding to the aliased table or field. For table aliases, the detector inserts an edge between the table alias node and each node of the base graph corresponding to a field of the table that is indicated in the database query. The detector evaluates the augmented graph for the presence of cycles that indicate that the database query(ies) represented in nodes therein include conflicting aliases.

A system and method for extracting structured key information from diverse document types using large multimodal models (LMMs) is disclosed. The invention employs a zero-shot analysis to identify candidate keys within an input document, then selects a document schema from a document schema database based on the identified keys. The LMM is prompted with the selected document schema to generate structured key-value pairs, with field constraints enforced by the document schema. Relationships among extracted keys are mapped to a graph representation, enabling robust handling of complex document layouts. The system supports nested structures, tabular data, and alias definitions for fields, and can update document schemas based on ground truth feedback. The resulting structured output is provided in a machine-readable format, enabling reliable and scalable document understanding across varied domains such as invoices, health cards, and driving licenses.

The invention discloses a multi-language large model dialogue optimization method and system fused with a knowledge graph, relates to the technical field of natural language processing and artificial intelligence dialogues, and is used for solving the problems of named entity recognition, time-varying attribute processing and dynamic updating of the knowledge graph in cross-language dialogues. And performing word-by-word scanning on each round of dialogue text through a multi-language naming mention extractor to form a traceable mention index. And performing cross-language retrieval and candidate entity positioning in the knowledge graph through a multi-language pre-training semantic model and an alias matching path. And for time-varying attributes and title changes, priority graph adjustment is carried out based on time slice windows and tense evidences, and smooth transition between new titles and old titles is guaranteed. And the accuracy and the stability of the final dialogue response are ensured by constructing a sparse cost matrix and an uncertainty re-discrimination process. According to the method, the problem of title switching in a dialogue system under multiple contexts is effectively solved, and the application effect of the knowledge graph in dialogues is improved.

The invention discloses a database system construction method and system based on new energy centralized control, and the method comprises the steps: employing a MySQL / PostgreSQL cluster to construct a historical library, constructing a real-time library through Redis, and achieving the cooperation of historical data storage and real-time data processing; the method comprises the following steps of: dividing data according to applications, and defining a multi-table structure; (2) realizing data hierarchical organization by adopting a multi-level name domain; a historical library and real-time library conversion service is configured, and single-table / multi-table data import is supported; an I / IV region security partition architecture is established, and data security interaction is realized through a bidirectional isolation synchronization mechanism; according to the system, through collaborative design of a relational database and a memory database, mass data storage and real-time response requirements are considered, a structured alias domain is adopted to realize accurate data management, and the requirements of a new energy centralized control system on data processing efficiency and security are met.

The invention relates to the technical field of computers, in particular to an enterprise private data standardization preprocessing system based on knowledge graph driving, and the method comprises a preprocessing module which is used for carrying out cleaning and standardization preprocessing on collected enterprise private text data to generate standardization text data; the word embedding generation module is used for training a word embedding model based on the standardized text data and generating word vector representation of the text; the named entity recognition module is used for recognizing a preset category of named entities in the standardized text data; the triple extraction module is used for executing open type information extraction on the standardized text data to obtain a relation triple; the entity deduplication module is used for performing deduplication resolution on entities in the relation triple extraction result; the relation clustering module is used for carrying out relation type classification clustering on the relation triple subjected to duplicate removal processing; and the graph construction module is used for constructing a knowledge graph according to the classified and clustered relation triples. According to the method, the problems of entity ambiguity, relation redundancy and unstable atlas construction caused by scattered sources, heterogeneous formats, high noise and repetition and mixed use of alias / pronouns of enterprise private data in the prior art can be solved.

The invention discloses a Hadoop tenant-level encryption isolation implementation method, and aims to solve the problems of single key leakage risk, namespace planarization, encryption area unauthorized binding, no tenant dimension auditing and the like existing in an existing Ranger-KMS scheme. The method comprises the following steps: creating an independent master key for each tenant to realize physical isolation; the key alias, the encryption area paths and the strategy resources are forced to carry tenant prefixes, and the consistency is verified; a tenant context is transmitted through a thread local variable; when an encryption area is created, tenant attributes are persisted, and operation consistency is verified; and the key plaintext is only stored in the KMS memory and is safely reset after being used. According to the method, full-dimension isolation of keys, data, strategies and auditing is realized, single-tenant key leakage does not influence the cluster, unauthorized access and information leakage are completely eradicated, compliance auditing requirements are met, single-cluster multi-tenant safe coexistence is supported, and hardware cost is reduced.

The present invention is a system and method for machine-to-machine communication in a Zero Trust environment. The instant invention describes a platform implementation that disables threat actors and their methods that target workload credentials. The platform is an Automated Moving Target Defense (AMTD) platform that creates sidecars that contain algorithms for creating secure keys from user specified dynamic elements, a machine alias ID (MAID), an encryption library, and an envoy proxy. The sidecars are utilized to control access to, and secure messaging traffic between, entities in a non-trusted environment.

The invention provides a computer system and method for supporting multi-language file processing. The computer system comprises a storage unit and a processing unit. The storage unit stores a graphical user interface (GUI) program and a file. The processing unit loads a GUI program from the storage unit to perform the following steps: receiving a file name of a file, where the file name is represented in a first language and follows a first character coding standard; establishing an alias for the file name, where the alias is expressed in the second country language and follows the first character coding standard; connecting the alias to the file such that both the file name and the alias refer to the file; and converting the alias to conform to a second character coding standard so as to start underlying processing conforming to the second character coding standard for the file referenced by the alias.

The invention relates to the technical field of information security and cryptography, and provides a distributed digital identity account processing method and device and electronic equipment. The method comprises the following steps: receiving an alias registration request sent by a first QVI mechanism; creating a user account tree based on the first account association information corresponding to the first user; the user account tree is a Merkel tree comprising at least one pair of leaf nodes, determining a first alias corresponding to the first user, binding the first alias with the user account tree, and generating a first identity certificate; at least combining the first root hash signature value of the user account tree with the hash value of the first identity certificate to generate a first association record, and synchronously storing the first association record in the block chain; and determining a corresponding user account tree according to the to-be-verified alias carried in the query request, generating a zero-knowledge proof based on the user account tree, and at least returning the zero-knowledge proof to the second user. According to the technical scheme, the AID account verification process can be simplified, and the user experience is improved.

Implementations described herein relate to a device identifier composition engine (DICE) 3-layer architecture. In some implementations, a device may include a secure computing environment including a hardware root of trust (HRoT) DICE component. The secure computing environment may include a DICE layer 0 component configured to derive a DICE identity key. The secure computing environment may include a DICE layer 1 component configured to derive a DICE alias key based on the DICE identity key. The secure computing environment may include a controller configured to receive an update to firmware of a component. The controller may be configured to update the firmware of the component based on receiving the update. The controller may be configured to update one or more keys of the component or one or more keys of one or more components above the component in a layer stack.

The invention provides a database updating method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, in particular to the technical field of databases. The method comprises the steps of obtaining an original data table; performing full-amount snapshot on data in the original data table, generating a second vector for the full-amount snapshot data by adopting a new embedding model, and storing the second vector and the original data into a new data table; for newly written data, adopting a new embedding model to generate a new vector, and storing the new vector into the newly-built message queue, so as to write the new vector into the newly-built data table through the message queue; and when the number of the to-be-processed messages in the message queue reaches a preset threshold value, switching the table alias of the data table from the original data table to the new data table so as to switch the read-write operation from the original data table to the new data table. According to the method and the device, the whole upgrading process is non-sensitive, and the influence on service operation is greatly reduced.

The application provides a smart home layered intention analysis and safe execution method and system and a storage medium, and relates to the technical field of smart home control. The method analyzes natural language into structured intention by constructing control context and home capability graph; adopts a layered mechanism to constrain retrieval candidate entities and calculate relevance score; performs risk scoring on control plan based on five dimensions of device risk level, control range, remote access state, time period and instruction conflict state, and adopts a hierarchical confirmation strategy; generates an execution graph and performs state checking, automatically reverts when a strong consistency scene fails; stores the correction result as personalized preference and sets a confidence decay rule. The application can significantly reduce the range of candidate devices, support contextual dialogue, control high-risk devices in stages, reduce the risk of miscontrol, ensure the consistency of complex scene execution, continuously improve the accuracy of alias recognition, and thus improve the efficiency, safety and user experience of smart home control.

This invention discloses a multilingual large-scale model dialogue optimization method and system integrating knowledge graphs, belonging to the fields of natural language processing and artificial intelligence dialogue technology. It addresses the problems of named entity recognition, time-varying attribute processing, and dynamic knowledge graph updates in cross-language dialogues. A multilingual named mention extractor scans each round of dialogue text word-by-word, forming a traceable mention index. Cross-language retrieval and candidate entity localization in the knowledge graph are performed using a multilingual pre-trained semantic model and alias matching paths. For time-varying attributes and title changes, priority graph adjustment is performed based on time slice windows and temporal evidence to ensure a smooth transition between old and new titles. The accuracy and stability of the final dialogue response are ensured by constructing a sparse cost matrix and an uncertainty re-discrimination process. This invention effectively solves the title switching problem in multi-context dialogue systems and improves the application effect of knowledge graphs in dialogue.

The application discloses a video point information standard management method and system based on reverse geographical joint checking, which comprises the following steps: performing joint checking on name semantics and geographical semantics through reverse geographical analysis results of latitude and longitude, and calculating geographical consistency scores; and based on the geographical consistency scores and the standard entity set, automatically completing the missing device attributes. Through multi-field preprocessing + candidate slot map joint modeling, the application can fully utilize the complementary information in the original code, attributes, latitude and longitude, and installation description; the BERT-BiGRU-CRF model and its training process are disclosed through prompting enhancement, which can avoid the problem of insufficient disclosure of the entity recognition model, and improve the entity recognition accuracy of non-standard point names; through the dynamic graph updating mechanism, preferably in the incremental updating mode, the application can continuously absorb new aliases, new device types and artificial review results, and avoid long-term static failure of the knowledge graph.

The invention relates to a reverse analysis method and device for SQL statements, equipment and a storage medium. The method comprises the steps that an SQL statement is preprocessed, and an annotation text in the SQL statement is removed; analyzing the preprocessed SQL statement to obtain a plurality of variables; integrating the plurality of variables to obtain a logic aperture of the insertion table; combining the logic calibers of the plurality of versions to obtain a unified logic caliber of the corresponding insertion table; under the condition that the sub-query identification variable represents that the temporary table exists in the preprocessed SQL statement, based on a unified logic caliber of a result table, penetrating through a middle temporary table in the preprocessed SQL statement layer by layer in a recursive mode; and calling the field processing logic of the intermediate temporary table in the table processing logic variable and the source table name corresponding to the intermediate temporary table in the table alias variable, combining the field processing logic and the source table name to the unified logic caliber of the result table, and outputting the result table to a specified file according to a preset format. SQL analysis traceability can be automatically completed, and the traceability efficiency is improved.

A method is presented which enables a controlled mechanism of applying the required set of settings, e.g., for cloud-based network infrastructure, by means of “profiles”. Infrastructure Management Service (IMS) applies one or more of Compute profile, Networking profile, Storage profile, Accelerator profile, and Application (“App”) profile to cloud infrastructure. The following set of procedures are defined to achieve the profile-based infrastructure management: a) profile definition; b) cloud-infrastructure-preparation based on profile(s); c) cloud audit and monitoring; and d) cloud preparation based on capability. Applying of a profile can involve one or more of: updating the BIOS settings, e.g., using Intelligent Platform Management Interface (IPMI) commands; updating the GRUB settings; updating the system / kernel parameters; updating interfaces (e.g., alias, bonding, etc.); creating required resources (e.g., virtual functions (VFs) and corresponding bindings); creating resource maps to be used by plug-ins; and running any scripts for custom needs of the RAN application.

Various systems and methods of anonymously conducting a secured payment transaction between a consumer and a merchant are disclosed. The methods can be carried out at a transaction code computer in communication with an alias directory. According to the method a transaction code computer receives a request for a dynamic transaction code from a merchant computer. The request includes a merchant alias identifier. The transaction code computer queries an alias directory storing merchant information details. The transaction code computer validates the merchant with the alias directory based on the merchant alias identifier. The transaction code computer generates the dynamic transaction code and transmits a response to the request for the dynamic transaction code to the merchant computer.

The application discloses a Text-to-SQL-oriented SQL generation quality evaluation method and system, and the evaluation method comprises the following steps: obtaining to-be-evaluated generated SQL, reference SQL and execution environment information; performing standardized processing on the generated SQL and the reference SQL; splitting the standardized generated SQL and the standardized reference SQL according to preset key clauses, and calculating a structure matching score according to preset weights of the key clauses to obtain an optimized accurate matching rate EM+; executing the generated SQL and the reference SQL, calculating an execution deviation score based on column mapping and result set comparison to obtain an optimized execution accuracy EX+; and outputting at least one of EM+ and EX+ as a SQL generation quality evaluation result. The application can solve the problems that existing evaluation indexes are not sensitive to aliases, equivalent expressions and partial errors or are too rough, and can realize fine-grained, interpretable and extensible evaluation of SQL generation quality.

The application discloses a new word and a first occurrence event recognition method and device, wherein the method comprises the following steps: obtaining hot-line work order text data according to a preset period, and preprocessing the hot-line work order text data to obtain a structured text stream; performing word segmentation and sliding window processing on the text stream to obtain an initial phrase candidate set; performing statistical access screening on the initial phrase candidate set, and performing alias merging on the candidate phrases passing the statistical access by using consistency rules of specified dimensions to obtain a word candidate set; updating a current space-time reference baseline based on the word candidate set, and recalculating historical full-amount data according to a specified fixed period to re-calibrate the space-time reference baseline; and determining whether there is a new word in the word candidate set and whether there is a first occurrence event based on the re-calibrated space-time reference baseline. Based on the unified space-time reference baseline, the new word and the first occurrence can be accurately and timely determined.

The application relates to an entity matching method, system, device and medium based on word frequency, wherein the method comprises the following steps: performing word segmentation on aliases in a plurality of entity data to obtain a first word segmentation list and an alias word set, counting word frequency data of words in the alias word set, removing city words existing in the first word segmentation list to obtain a second word segmentation list, judging whether the words in the second word segmentation list are common words according to the word frequency data, processing the words in the second word segmentation list according to the judgment result, obtaining alias keywords corresponding to the aliases, and querying whether the alias keywords exist in a text corpus; if the alias keywords exist, an entity corresponding to the alias keywords is recognized in the text corpus. Through the application, the problems of missed recognition caused by alias simplification and alias synonym misjudgment are solved. The alias keywords are obtained based on the word frequency of the words in the aliases, entity matching is more accurate, and the accuracy of entity matching is improved.