215 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.

The invention discloses a graph theory-based industrial internet identification system full-process tracing method, which realizes full-process tracing in a supply chain by introducing identifier fields into metadata and constructing a directed graph structure. The identifier fields include fields with similar representations for representing associations of the product upstream and downstream of the supply chain. The system queries across enterprises through a graph traversal algorithm (such as depth-first search (DFS) or breadth-first search (BFS)), and tracks the full life cycle of a product. The method supports attribute pointing code management, is used for tracing multi-attribute information (such as allocation weight, time and the like) of a product, solves cross-enterprise and cross-system coding differences through an alias mechanism, and simplifies a tracing process. The method has a flexible traceability path setting capability, can monitor the product circulation process in real time, gives out an early warning when an abnormality is found, and improves the transparency and safety of a supply chain.

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.

A cloud computing platform provides zero trust network access as a service to customers that maintain applications on-premises. In this context, the cloud computing platform may associate customers and / or applications with specific service proxies, and add an abstraction layer for network access that maps an alias domain for each customer and / or application to a network load balancer associated with the specific service proxies associated with the corresponding application(s). This approach advantageously simplifies the configuration of service proxies at the cloud computing platform by permitting dedicated relationships among network load balancers, specific service proxies, and specific applications, while concurrently reducing or avoiding the administrative burden on customers of updating network pointers when the clusters of service proxies are periodically reconfigured to adjust to varying user traffic.

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 provides a large-scale-oriented IPv6 target address generation method and a large-scale-oriented IPv6 target address generation system. The method comprises the following steps: constructing an IPv6 seed address set based on an IPv6 capacity expansion strategy of sampling distribution and an IPv6 classification strategy based on an address structure; clustering the IPv6 seed address set to construct an IPv6 address space tree so as to generate a low-dimension IPv6 address mode set and a high-dimension IPv6 address mode set; generating an IPv6 target address set in the low-dimension IPv6 address mode space, and removing IPv6 alias addresses in the IPv6 target address set to obtain a non-alias target address set; a non-alias target address set in a low-dimension IPv6 address mode space is detected, an active high-dimension IPv6 address mode is screened out from a high-dimension IPv6 address mode set according to the detected IPv6 active address, an IPv6 target address set is generated in a corresponding space of the active high-dimension IPv6 address mode, IPv6 alias addresses are removed, and the IPv6 address mode is obtained. After a non-alias target address set is obtained, detecting the non-alias target address set and collecting responded IPv6 active addresses; and combining the IPv6 active addresses detected in all the seed address sets to form a final IPv6 active address set.

The present disclosure proposes computer implemented methods, devices and systems for implementing an addressing service for transactions associated with a distributed ledger, wherein an alias is provided for a client among one or more clients associated with the addressing service, the alias being specific to the client. The method comprises the steps ofobtaining or accessing a plurality of seed words; for a given alias associated with a given client among the one or more clients, encoding the alias and applying a hash function to the encoded alias to obtain a hash value; extracting a first series from the hash value; and determining at least one seed word from the plurality of seed words based on the first series, the at least one seed word representing a code for the given alias.

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.

The invention provides an inter-beam bunch signal aliasing calibration method based on a cavity probe. The inter-beam bunch signal aliasing calibration method comprises the following steps: acquiring a non-aliasing reference signal from a high repetition frequency free electron laser device; extracting a signal waveform of each beam bunch and a measurement result thereof from the aliasing-free reference signal; modeling to obtain a residual signal formula; obtaining a calibration result of the beam bunch based on a residual signal formula and a vector calibration algorithm according to the measurement result of the aliasing signal waveform and the standard waveform of the previous beam bunch; taking the next beam bunch as the current beam bunch, and returning to the step of obtaining the calibration result; and obtaining calibration results of all the beam bunches until all the beam bunches are calibrated. According to the method, the amplitude-phase characteristics of the attenuation wake of the adjacent beam bunches are modeled and compensated through the vector calibration algorithm, the time domain aliasing effect in the high-repetition-frequency free electron laser device is effectively eliminated, and the phase absolute deviation measured by the beam arrival time of the cavity probe is reduced to the femtosecond magnitude.

Disclosed in some examples are methods, systems, and devices for authenticating a firmware object on a device and in some examples to safeguard the attestation process from the execution of malicious firmware. In some examples, a firmware update process may, in addition to updating the firmware on the device, write a hash of the authentic firmware code in a secure storage device (e.g., a register). This may be done in some examples in a protected environment (e.g., a trusted execution environment or a protected firmware update process). Upon first boot after the update, a firmware update checker compares the firmware object that is booted with the value of the secure storage device. If the values match, the alias certificate may be regenerated, and the boot continues. If the values do not match, then the alias certificate may not be regenerated, and the system may have an authenticity failure because the key and the certificate do not match.

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.

According to the branch prediction method provided by the invention, the branch prediction result is obtained by indexing the historical branch prediction instructions in the branch prediction condition table, and the relevance between the historical branch prediction instructions can be well utilized, so that the success rate of branch prediction is greatly improved; meanwhile, the last four bits of the branch prediction instruction and values in the global historical register are subjected to logical operation, an operation value is obtained and then indexed, and the influence of the alias of the branch prediction instruction on branch prediction can be reduced; meanwhile, when the branch prediction result is skipping and the operation code of the branch prediction result is matched with the operation code of the indexed historical branch prediction instruction, the branch prediction result is trusted, so that the branch prediction accuracy is further improved; and moreover, the jump address is obtained by adopting a direct operation method, so that the area overhead and the delay caused by storing a large number of branch addresses by the BTB (Branch Target Buffer) can be saved.

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.

Generating an access point certificate based on a graph that defines relationships between an access point and at least one domain is described. A computing device may generate a graph that defines relationships between a domain and multiple different access points including a serving access point and one or more fallback access points. A device may generate a certificate for accessing data via the domain based on the relationships between the domain and the one or more fallback access points. A device may control access to the data using the certificate. The graph may define a relationship between a network address, an access point, and one or more records associated with at least one domain. Further, the graph may define a first relationship between a network address and a record associated with a domain and a second relationship between the network address and an alias record associated with the domain.

The invention relates to an IPv6 side equipment router alias information detection method, device and equipment. According to the method, a public IPv6 router alias address data set is taken as a target, Tracroute detection is carried out on a target address, TCP, UDP and ICMP message packets are sent, a detection host analyzes Tracroute path records of seed alias, the paths which have wide structural similarity but are different only in a single IP hop address in the paths are identified, the paths are marked as candidate alias pairs, and the candidate alias pairs are marked as candidate alias pairs. Meanwhile, a feature set is established for training, so that an alias classification model is established, and whether the target router pair is an alias pair or not is determined. Compared with the prior art, the method has the advantages that the address of the IPv6 router is detected within the Internet range, alias information of the network router is correctly and efficiently classified, and effective technical and data support is provided for network surveying and mapping and network security research.

The invention provides a cross-domain access method and system for a decentralized control system, computer equipment and a storage medium, and belongs to the technical field of cross-domain access control. The method comprises the steps of dividing security domains of a unit plant and a public system; determining a security domain to which the cross-domain access service belongs and control node information; constructing a mapping relation between the alias points and the data source points and a privilege point list; registering cross-domain access service node information at the control node; creating a virtual data node in a security domain where the alias point is located so as to bind a real-time synchronization channel of the data source point; under the condition that a control node initiates a cross-domain request, a requester security domain identifier and a data point unique ID are added and sent to a cross-domain service node; and under the condition that the cross-domain service node verifies that the request security domain is valid, stripping the security domain identifier and executing the target operation. The problem of mutual operation between units caused by configuration errors is avoided, the stability and safety of the operation units are improved, and then the continuity of power plant production is improved.

The invention discloses relation modeling for network address domains. Generating access point credentials based on a graph defining a relationship between an access point and at least one domain is described. A computing device may generate a graph defining relationships between a domain and a plurality of different access points, including a serving access point and one or more backup access points. The device may generate credentials for accessing the data via the domain based on a relationship between the domain and one or more backup access points. The device may use the credentials to control access to the data. The graph may define a relationship between the network address, the access point, and one or more records associated with the at least one domain. Further, the graph may define a first relationship between the network address and a record associated with the domain and a second relationship between the network address and an alias record associated with the domain.

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.

The embodiment of the invention discloses a remote procedure calling method, system and device and a storage medium. According to the technical scheme provided by the embodiment of the invention, the method comprises the steps: obtaining a to-be-sent RPC request message, querying a pre-constructed alias management mapping table based on a full-definition name of a target class called by the RPC request message, and determining an alias and a serializer corresponding to the target class from the serialization information of the target class stored in the alias management mapping table; serializing the RPC request message based on a serializer, generating a message byte stream corresponding to the RPC request message, and writing the alias into the message byte stream; and sending the message byte stream to the target node, and receiving response information returned by the target node based on the message byte stream. By adopting the technical means, the development efficiency and the calling efficiency of the remote procedure calling method can be improved, and the use experience of the remote procedure calling service is improved.

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 relates to the technical field of artificial intelligence, and particularly provides a visual network optimization AI assistant implementation method and device, based on Transform and LLM, the method comprises the following steps: S1, a database modeling module carries out dimension definition, index definition and term library construction; s2, the voice interaction module selects a basic model to carry out data fine tuning and keyword enhancement; s3, the LLM-SQL generation module uses a GPT-4 or an open source LLM as a base; s4, the SQL correction module carries out logic verification and term replacement; s5, establishing a mapping table of aliases and actual fields by a field mapping module, and expanding dynamic fields; and S6, performing chart engine and geographical rendering by a multi-modal presentation module. Compared with the prior art, the method has the advantages that the development cost can be remarkably reduced, the user query flexibility and the data presentation intuition are improved, and the network optimization decision is effectively supported.

Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: performing static analysis of program source code defining a computer program, wherein the computer program comprises a pointer operation callee and at least one caller that can pass a pointer parameter to the pointer operation callee; generating, in dependence on the static analysis of program source code, binary code executable so that the pointer operation callee, in runtime, performs a runtime check for determining pointer alias status of the pointer operation callee; and generating, in dependence on the static analysis of program source code, executable binary code executable so that the pointer operation callee, in runtime, performs selecting and activating an executable code path in dependence on a result of the runtime check.

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.