32 results about "Trie" patented technology

Techniques for constraining a language model's generation / decoding process using a finite state machine are described. A finite state machine may represent information corresponding to APIs, arguments and argument values that are available / supported by the system. In some embodiments, a language model (LM) is constrained to generate tokens representing valid API calls based on the finite state machine. The system may enable generation of argument values from a defined set or free-form generation of argument values. The system may also enable unconstrained generation of a response by the LM. In some embodiments, a trie data structure is used to determine the possible next tokens that the LM can generate from.

The invention discloses a large language model reasoning acceleration method and device based on two-stage speculative decoding and a storage medium, and the method comprises the steps: constructing and initializing a Trie tree, and inserting a historical corpus, and phrase sequences in a document library or a code library into the Trie tree one by one; in the reasoning process, longest prefix matching is carried out based on a Trie tree, and a candidate draft sequence is generated by adopting branch backtracking and recursive search; performing confidence evaluation on the candidate draft sequence, calculating a joint confidence score of the sequence through probability multiplication and a Top-K screening mechanism, and judging whether the joint confidence score reaches a confidence threshold; if the accumulated confidence of the candidate sequence reaches a threshold value, skipping a small model generation stage, and directly entering large model verification; otherwise, entering a small model draft completion stage; and the final large model takes the replaced and updated draft sequence as final output. According to the method, adaptive acceleration of the decoding process can be realized, and the long text reasoning delay of the large language model is remarkably reduced while the generation quality is ensured.

Techniques for constraining the results of a generative language model to valid information using knowledge-grounded documentation. A generative language model may generate invalid results, including compound entities and incorrect entity relations. The techniques include, for a given user inquiry, determining a set of documented information, from a particular knowledge base, that corresponds to the user inquiry. The techniques further include determining a subgraph from a knowledge graph representing the knowledge base, as well as determining a trie data structure representation of the set of documented information. The user inquiry and subgraph are provided as input to a trained generative language model for generating a response to the user inquiry. The techniques include using the trie data structure to validate that the generated response corresponds to real information from the set of documented information.

The invention discloses a multi-modal fusion short message compliance and security dual auditing method and system, and the method comprises the steps: encrypting account information through employing an irreversible algorithm based on SHA256 and a random salt value, and decomposing the content of a short message into a text stream, a link stream and a symbol stream through employing a regular expression; traversing each character in the short message content by adopting a prefix mode based on a Trie tree in combination with an AC automaton algorithm to detect sensitive words; performing symbol semantic classification mapping and analysis on the special symbol feature data extracted from the symbol stream; carrying out sending behavior analysis on the text feature data extracted from the text stream; performing special detection on link feature data extracted from the link stream; based on the factors corresponding to the sensitive words, the semantics, the behaviors and the links and the weights of the factors, a multi-modal feature fusion decision risk assessment algorithm is adopted to output a risk score value and a risk decision rule of the risk score value so as to execute short message interception operation or short message release operation. According to the invention, full-dimension perception and dynamic defense of risks can be realized.

The invention relates to the field of data access, and particularly provides an MPT-based block chain database system, a data access method, a terminal and a medium, the system comprises a native MPT storage engine used for realizing an MPT node structure in a disk and a memory, and the node structure comprises branch nodes, extension nodes and leaf nodes; the asynchronous I / O module is used for realizing non-blocking disk operation based on Linux iouring; the file system bypass module is used for supporting direct access to the block device; the versioning concurrency control module is used for realizing lock-free reading through an immutable Trie structure and atomic pointer updating; and the dynamic compression module is used for dynamically adjusting a historical data retention strategy according to the disk space utilization rate. The MPT structure storage engine is realized, basic data support is provided for a high-performance block chain system, serialization overhead is eliminated, and storage efficiency is improved.

This application discloses techniques related to tree data structures capable of storing information indicative of database key codes. A computer system can operate a database. The computer system can store a multi-level tree data structure capable of being used to perform key code lookups for the database. In various cases, the multi-level tree data structure can be stored in system memory as a plurality of sub-tree data structures, each sub-tree data structure comprising a set of linked nodes. A given one of the plurality of sub-tree data structures can be stored in system memory as a respective contiguous block of information. The computer system can access the respective contiguous block of a first particular sub-tree data structure encompassing a particular range of levels in the multi-level tree data structure. The access can be performed without accessing one or more other sub-tree data structures encompassing one or more levels within the particular range of levels.

The application belongs to the field of natural language processing, and particularly relates to a text key phrase extraction method, a storage medium and a device that integrate inter-sentence correlation, comprising: extracting a nominal phrase in a part-of-speech combination mode; filtering the nominal phrase by combining two Trie trees to obtain a candidate phrase set; calculating a global semantic similarity score of the candidate phrase; clustering each sentence to obtain a sentence cluster containing different semantic information; and sorting the candidate phrases in the sentence cluster according to the global semantic similarity score of the candidate phrase to obtain a key phrase set; the application integrates the inter-sentence relationship in the unsupervised key phrase extraction model based on embedding, improves the accuracy of the model, and constructs different Trie trees to calculate mutual information and left and right information entropy as a candidate phrase extraction method in the key phrase extraction model, thereby reducing the probability of incomplete semantic information appearing in the extracted candidate phrase set.

The invention relates to the technical field of computers, and discloses a high-load micro-service starting method and system, electronic equipment and a storage medium, and the method comprises the steps: executing a hierarchical preloading mechanism, initializing a connection pool, and building a preset minimum idle connection number; checking algorithm optimization is executed, a client feature Trie tree is constructed, root nodes are initialized, child nodes are inserted in sequence according to character string characters, new nodes are created when the child nodes are missing, and the nodes are marked as word ending when character strings are ended; executing request verification mechanism optimization, and returning an error response or an unauthorized response when verification fails; probe parameter dynamic adjustment is executed, and the survival probe detection interval is dynamically adjusted according to the operation indexes; according to the method and the device, the problems of resource waste, low processing efficiency and insufficient stability in a traditional scheme are solved, and reliable technical guarantee is provided for a high-load micro-service scene.

Described are an encoding method and system for ROAs. The encoding method includes the following steps: given a set of authorized IP prefixes an AS which are maintained with an IP address trie. By specifying a sequence of hanging levels on the IP address trie, it is divided into a set of non-overlapping sub-trees, each rooted at a hanging level. A node on a hanging level uniquely defines a sub-tree rooted at it, whose prefix can be encoded as the identifier of this sub-tree. All authorized prefixes covered by a sub-tree can be encoded into a bitmap of 2h bits, where h is the height of this sub-tree. Thus, the set of authorized IP prefixes of an AS is encoded into several tuples (identifier, bitmap).

Embodiments of the present application disclose a word completion method applied to a search scenario to complete an incomplete word input by a user. The method of the embodiments of the present application is based on an improved dictionary tree, hot words are stored in part nodes of the dictionary tree, in the word completion method, a target node matching the string is searched in the dictionary tree Trie, and at least one completed word is output to the user based on the hot words stored in the target node. The word completion efficiency can be improved, and the user is prevented from being recommended words when inputting a too-short string.

This application relates to the field of PLC programming technology, and in particular to a fast symbol retrieval method for ultra-large multi-station PLC projects. The method involves data parsing, symbol metadata standardization, and fragment preprocessing of the PLC project file to obtain standardized SymbolMeta fragment data. Based on the standardized SymbolMeta fragment data, a three-level hierarchical index architecture is constructed, consisting of station-level hash routing, task-level compressed prefix Trie trees, and symbol-level differential encoded inverted lists. According to user query conditions, station-level fast pruning, task-level Trie tree matching, and symbol-level differential decoding aggregation are performed sequentially within the three-level hierarchical index architecture to generate structured retrieval results. Incremental updates are performed on the three-level hierarchical index architecture based on the PLC project's modification instructions. This solves the problems of high latency, weak fuzzy matching capability, high resource consumption, and delayed updates in retrieval of symbols exceeding 100,000, achieving millisecond-level accurate positioning.

This invention belongs to the field of blockchain technology, specifically relating to a semantic identifier blockchain retrieval method and system for large-scale distributed data. This invention designs a unified semantic identifier model, mapping data records from different sources and in different formats to multi-level scalable semantic paths. It constructs a MIR tree forest, integrating the organization of Trie and the verifiability of Merkle, with each scenario as the root. Only the root hash of each scenario or its aggregate root is maintained in the block header, thereby achieving overall constraint on the state of large-scale off-chain semantic indexes while maintaining lightweight on-chain storage overhead. Simultaneously, this invention designs corresponding index traversal and verification object construction mechanisms around various semantic retrieval modes, enabling clients to verify the correctness of target records with only limited path and node hash information. This provides a new technical path for unified semantic management and efficient verifiable retrieval of multi-source heterogeneous data in the HSB environment.

The invention discloses a ten-million-level domain name rule quick loading method based on distributed compiling, which comprises the following steps of: reading and analyzing a rule file containing an accurate domain name and an extensive domain name, and distributing rule analysis result data into a hash table according to a grouping number to obtain a plurality of rule groups; according to the grouping number, compiling threads with the same number are created to form a compiling thread pool; traversing all the rule groups, allocating a compiling thread for each rule group to execute a compiling task, and performing distributed parallel compiling by using a Hyperscan state machine and a Trie tree; receiving an input domain name character string and determining a rule group to which the input domain name character string belongs; if yes, the Hyperscan state machine of the rule group is used for preliminary matching, and if yes, the Trie tree of the rule group is used for accurate matching. According to the method, the problem that a Hyperscan lightweight interface cannot precisely limit a domain name is solved, and rapid loading of a ten-million-level domain name rule is realized.

Method includes obtaining historical document images including text that correspond to different document classes; and generating a dictionary using text of the historical document images. The dictionary includes base words occurring with a greatest frequency in each document class. The base words are extracted from the text of the historical document images and arranged in datasets by a document class, where each dataset includes the base words of a same document class that occur with the greatest frequency within that document class. Trie structure is generated using the base words of the datasets that occur with a greatest frequency in each dataset. The trie structure includes internal nodes including root node and leaf nodes in which keys corresponding to the base words occurring with the greatest frequency in each dataset are respectively stored in predefined order. The trie structure is searchable in the predefined order starting with the root node.

This application discloses a method for generating and decompressing compressed log files, and an apparatus for doing so, relating to the field of data processing technology. Based on obtaining a source log file and a trie, and generating an initial compressed log file, the method identifies the first command-line interface log from multiple command-line interface logs included in the source log file. Then, the log timestamp in the first command-line interface log is determined as the base timestamp and written into the header of the initial compressed log file. Next, each command-line interface log is compressed according to the trie and the base timestamp to generate corresponding log tag values. Finally, each log tag value is written into the data area of ​​the initial compressed log file, and the trie is written into the trie area of ​​the initial compressed log file to generate the final compressed log file. This solves the problem of wasted storage space.

An IP address lookup method applied to IPv6, the method comprising: constructing a lookup data structure tree based on a multi-bit Trie tree, wherein each internal Trie node with a real node corresponds to one or more IP prefixes in an IP forwarding table; determining a mappable pipeline stage range of each node according to a reverse distance of each node in the lookup data structure tree, a pipeline stage where a child node is located, a path length from the node to a root node, and a position of a pipeline stage where a parent node is located; wherein the reverse distance is defined as a maximum distance between the node and all successor leaf nodes thereof; dynamically mapping each node to an independent storage resource of a corresponding pipeline stage according to the mappable pipeline stage range and a storage space condition of each pipeline stage; and performing IP address lookup in parallel in each pipeline stage according to the node mapping result to realize pipeline parallel lookup. The method can improve lookup efficiency.

This application discloses a method, apparatus, device, storage medium, and product for adjusting a trie, relating to the field of data storage technology. The method for adjusting a trie includes: after the nodes of the trie are updated, obtaining the occurrence count of each node in the current trie; determining whether there is a node in the trie whose occurrence count is greater than a preset threshold; if there is a node whose occurrence count is greater than the preset threshold, constructing that node and at least one of its parent nodes as a shared node of the trie, and based on the shared node, merging the child nodes of that node to obtain a structurally adjusted trie. This application compresses frequently accessed nodes into shared nodes, realizing shared storage of characters rather than independent character storage, thereby improving the space utilization of the trie, reducing the redundancy of character storage in the trie, and improving the storage efficiency of the trie.

An automaton management method and device, in which a computational node constructs a fractal automaton according to first information, the first information comprises at least one first pattern string, the first pattern string comprises at least one character, a first dictionary tree comprises a plurality of nodes, and if at least one first pattern string comprises at least one universal character, the first pattern string comprises at least one character; the plurality of nodes comprise a first root node, at least one second root node and a plurality of non-root nodes, the first root node is empty, one second root node corresponds to one universal character, and the non-root nodes correspond to one non-universal character; the failure pointer of the first root node or the at least one second root node points to itself, the plurality of non-root nodes comprise a first non-root node, the first non-root node is such as a father node, a brother node or a child node of the second root node, and the failure pointer of the first non-root node points to the second root node. The optimized automaton structure is provided through the method, so that the automaton can support fuzzy matching, and operation and maintenance management is facilitated.

This application provides a data parsing method, apparatus, electronic device, and storage device. The data parsing method includes: acquiring a data file; the data file containing several interrelated data elements; constructing a trie based on the data file; determining the data chain containing the target data element based on the trie; and generating branch data based on the data chain containing the target data element. The technical solution provided by this application can easily reconstruct the data chain corresponding to the target data element and can realize the function of adding branch data to the original data chain, providing convenience for reviewing data files or adding new ideas, and improving data parsing efficiency.

The invention discloses a rapid heterogeneous configuration text matching method based on skeleton indexes and frozen semantic anchor points, which comprises the following steps of: firstly, constructing a self-adaptive structure dictionary tree (Trie) and an inverted index of a multi-manufacturer configuration template library, and analyzing a text into a structure operator and a parameter placeholder; in the real-time detection stage, a scanning mechanism based on maximum prefix matching and a fuzzy automaton (Fuzzy Automaton) is adopted, and automatic error correction and mixed feature sequence extraction of heterogeneous texts are achieved; then executing dual-channel vectorization, generating sparse vectors for the structure sequence by adopting position weighted N-gram hash coding, and generating semantic dense vectors for parameter instances by utilizing a pre-training language model of frozen parameters in combination with cue words; meanwhile, a type semantic anchor point space based on natural language description is constructed, and zero sample type verification is achieved; and finally, completing optimal matching through a cascading strategy of structure rapid preliminary screening, parameter semantic fine arrangement and dynamic weighted comprehensive scoring. According to the method, the command skeleton and the parameter semantics are decoupled, so that the high efficiency of retrieval and the generalization of semantic understanding are considered, and the accuracy and robustness of heterogeneous configuration text matching are remarkably improved.

The invention provides a rapid industrial chain classification method and system based on a memory database, and relates to the technical field of financial science and technology and data processing. The method comprises the following steps: analyzing massive industrial chain node rules, and extracting prefix modes of classification key identifiers such as tax classification codes to construct an industrial chain rule prefix tree (Trie tree); the method comprises the following steps: acquiring business data such as invoices of a target enterprise, extracting classification key identifiers actually involved in the business data, and matching in a Trie tree, thereby dynamically screening out a to-be-executed rule set in a minimum range; and loading target enterprise business data by utilizing a memory database (such as H2), executing the screened rule set in a memory environment, and outputting an industrial chain classification result. According to the method, the rule traversal range is greatly narrowed through the Trie tree, the disk I / O bottleneck is eliminated through the memory database, and millisecond-level real-time classification and verification of the enterprise industry chain attributes in the whole online credit process are achieved.

The application discloses a private communication method and system based on a dynamic dictionary and an adaptive security strategy. In view of the problems in the prior art, such as easy identification by an examination system for strong encryption, easy manual discovery for pure camouflage, low matching efficiency of a mobile terminal dictionary, and privacy leakage caused by cloud dependence of intelligent reply, three technical innovations are provided: 1) a low-delay real-time text stream matching of a mobile terminal mass word is realized through a Trie tree, and the time complexity is reduced to O(L); 2) an adaptive security strategy of a camouflage mode and an encryption mode is provided, a user can dynamically switch according to a scene, and the concealment of communication behavior and the absolute safety of content are considered; and 3) a completely localized reply assisting engine, real-time monitoring of trigger words and display of suggested replies, do not upload any user data throughout the process, and completely eliminate privacy leakage from the architecture. The application also supports multi-dictionary set management and encryption synchronization, and is suitable for private communication needs in scenes such as lovers and teams.

This invention discloses a data-driven method and system for estimating selectivity using the `like` predicate, relating to the field of query selectivity prediction technology for relational databases. The method includes the following steps: receiving a query statement containing a `like` predicate and determining the type of the `like` predicate; constructing a trie, finding the corresponding trie based on the type of the `like` predicate to convert the `like` predicate query into a numeric range predicate query; performing a similarity query in a cardinality estimation result database based on the numeric range predicate query; if there are similarity query results exceeding a set threshold, directly reusing the retrieved cardinality estimation results; if there are no similarity query results exceeding the set threshold, performing cardinality estimation using a data-driven model. This invention enables rapid cardinality estimation for SQL queries containing `like` predicates.

Systems and methods for performing inference for word or wordpiece tokenization are disclosed using a left-to-right longest-match-first greedy process. In some examples, the vocabulary may be organized into a trie structure in which each node includes a precomputed token or token_ID and a fail link, so that the tokenizer can parse the trie in a single pass to generate a list of only those tokens or token_IDs that correspond to the longest matching vocabulary entries in the sample string, without the need for backtracking. In some examples, the vocabulary may be organized into a trie in which each node has a fail link, and any node that would share token(s) or token_ID(s) of a preceding node is instead given a prev_match link that points back to a chain of nodes with those token(s) or token_ID(s).

Method includes obtaining historical document images including text that correspond to different document classes; and generating a dictionary using text of the historical document images. The dictionary includes base words occurring with a greatest frequency in each document class. The base words are extracted from the text of the historical document images and arranged in datasets by a document class, where each dataset includes the base words of a same document class that occur with the greatest frequency within that document class. Trie structure is generated using the base words of the datasets that occur with a greatest frequency in each dataset. The trie structure includes internal nodes including root node and leaf nodes in which keys corresponding to the base words occurring with the greatest frequency in each dataset are respectively stored in predefined order. The trie structure is searchable in the predefined order starting with the root node.

The invention discloses a method, a device and equipment for searching an egress sflow output port under an SONiC (SONiC) system, and the method comprises the steps: configuring a function switch obtained from redis configdb when hsflow is initialized; subscribing to the routing information in the redis appdb, and adding the obtained routing information to a Trie table; the method comprises the following steps of: acquiring and subscribing a hash key message in a configdb (Congigdb); in the original process of receiving and analyzing the netlink message by the hsflowd, adding predetermined information in an analysis data packet to obtain original packet information; wherein the analyzed predetermined information is determined according to a hash key obtained by subscription; searching the Trie table by using an LPM algorithm to find a next hop; and if the searched next hop is ECMP, calculating a hash value according to the analyzed original packet information, and selecting an output port according to the hash value. According to the invention, the egress sflow output port information is obtained by adopting a software implementation mode, so that an upper platform can conveniently manage, control and schedule the flow, and the superiority of the SONiC system is enhanced.

This invention discloses a training-free intelligent interaction system based on deterministic feature targeting and self-reflection. The core is deployed on consumer-grade terminals such as mobile phones, tablets, and computers, and is compatible with embedded chip deployment. The system replaces "recognition" and "understanding" with multimodal deterministic retrieval. All inputs are converted into deterministic feature identifiers, accurately compared with a local feature library, and output corresponding results or trigger preset rules. The system integrates core capabilities such as context memory, referential resolution, dual-mode interaction, dynamic reasoning path generation, deterministic deduction, and self-reflection, supporting multi-turn dialogue, cross-turn reasoning chain continuation, operation execution, and visual output. This invention transforms unstructured text in documents into logical constraint equations, achieves O(1) matching of massive fingerprint databases through Trie tree indexing, replaces linear calculations with rule boundary judgment, and achieves O(1) complexity logical contradiction detection and automatic correction through a reverse hash index tree. The global feature library supports offline construction from multiple channels such as public datasets, industry databases, customer-owned data, internet crawlers, manual input, and user feedback, without involving model training. The system solves the technical problems of existing intelligent interaction systems, such as reliance on cloud recognition, privacy leaks, uncontrollable output, and misleading multimodal functions.

The invention belongs to the technical field of computer information retrieval and data structure application, and relates to a quick matching method of fuzzy keywords based on a Trie tree, comprising a collaborative architecture of a variant Trie tree, a global quick failure bitmap and a multi-modal similarity calculation module, and a variant Trie tree node integrated local quick reachable cache to reuse a successful matching path; the global fast failure bitmap records invalid state-character pairs through 64-bit key values to realize cross-query path pruning; in the multi-modal similarity calculation, Chinese character phonetic form and font characteristics are fused, and an initial confusion matrix and a stroke difference punishment mechanism are combined, so that the matching precision is improved. Through a double-layer cache mechanism and a composite similarity model, the method significantly reduces the calculation redundancy on the premise of not sacrificing the accuracy. The method effectively improves the efficiency and expandability of fuzzy matching, and is suitable for a large-scale text processing scene.

The application discloses an intelligence intelligent question and answer method based on a knowledge graph, and utilizes a knowledge base to construct the knowledge graph; according to a military type database, entities and the relationship between the entities in the database are recognized, and based on a document type database, the knowledge graph is constructed; given a natural language question, entity library information is stored by utilizing a Trie tree, and entity retrieval is carried out according to an AC automatic machine algorithm; for entities that are not matched, Word2Vec algorithm is used for fuzzy matching of the entities; the problems involved in the natural language question are recognized based on a relationship template exhaustive mode, and the correspondence and pairing between the entities and query attribute items are realized; according to the returned entities and the relationship of the question, a query statement is converted and used as a structured query language of question and answer search, and a query result is returned. The application improves the feature entity extraction capability of the model, and improves the robustness and precision of the model.

The application discloses a kind of mass coordinate data conversion methods based on high gao POI data, comprising: based on the principle of quadtree index optimization rectangular search algorithm, and obtain POI data of research area;Research area is gridded, constructs research area grid point coordinate database, POI coordinate point is matched with database to determine the WGS-84 coordinate of POI coordinate point, and the WGS-84 coordinate of POI coordinate point that cannot be matched is obtained using bilinear interpolation method;Define chinese address element annotation set, use hidden Markov model to carry out word segmentation processing to source address information in POI data;The first four layers of address information after word segmentation processing are parsed using Trie tree model, and the remaining six layers of address information are parsed using state automaton, to finally obtain complete address information.The application expands the threshold of POI data, so that the acquired area information is more comprehensive and accurate;Effectively solve the deviation problem between the value obtained by gao API interface and the true value, realize the accurate correspondence between longitude and latitude value and real geographical position.