58 results about "Substring" patented technology

The invention relates to the technical field of electrical digital data processing, and discloses a statistical entropy and multi-factor fused text similarity data processing method, which comprises the following steps that: a processor extracts substring sets which do not contain maximum common values of a first data sequence and a second data sequence, and calculates the quadratic sum of the lengths of substrings to generate local statistical entropy; traversing the maximum common substring set to obtain storage address indexes of the maximum common substring set in the first data sequence memory space and the second data sequence memory space, and constructing a topological mapping vector of a mapping structure displacement relationship; calculating the total number of inverted pairs of the topology mapping vector by using a merge sorting algorithm, and generating a normalized topology dissipation index; and by taking the local statistical entropy as an information carrier and taking the topological dissipation index as a structural damping factor, executing nonlinear damping modulation operation to obtain a final similarity score, and solving the technical problem that the block-level displacement cannot be identified by linear scanning logic by quantizing topological entropy increase of data distributed in a storage space.

The application relates to a code detection method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a target code to be detected; performing string division on the target code to obtain a target substring sequence; obtaining a substring vector corresponding to each target substring in the target substring sequence to form a vector sequence; performing linear feature extraction on the vector sequence to obtain first extracted features, and performing nonlinear feature extraction on the vector sequence to obtain second extracted features; performing fusion processing on the first extracted features and the second extracted features to obtain fusion features; and performing code detection based on the fusion features to obtain a code detection result corresponding to the target code. A cloud server can use an artificial intelligence-based malicious code detection model to implement the code detection method of the application, thereby achieving the purpose of reducing network attacks. The method can improve the accuracy of malicious code detection.

The present application relates to the technical field of information security, and aims at the problems that password guessing based on probabilistic context-free grammar is difficult to identify multi-semantic patterns and the semantic guidance strength is uncontrollable, and proposes a password guessing method based on multi-semantic fusion of probabilistic context-free grammar: enumerating sub-strings in the training password, identifying semantic segments according to simple, date, vocabulary and name patterns and prioritizing disambiguation, dynamically planning segmentation according to the principle of maximum semantic coverage and least semantic segments, setting semantic enhancement parameters β for each semantic pattern during training to weight and normalize the count, and outputting the candidate password dictionary according to the probability priority queue during generation, which is suitable for efficient password guessing in offline password audit, password policy evaluation and penetration testing.

This invention provides a method for calculating semantic similarity based on adjacent word features, relating to the field of natural language processing. First, in the example word extraction module, example words are extracted from the example sentence and the sentence to be matched using the longest common substring algorithm. Second, in the example sentence processing module, word segmentation is performed on the example sentence excluding the example words, and part-of-speech tagging is applied to the example words. Then, in the feature extraction module, features are extracted from the words surrounding the example words in the example sentence. The correlation between the surrounding words and the example words and option words is calculated using a corpus. The calculated results are weighted and combined with their respective features to form the features of the example words and option words. Finally, in the option processing module, the part-of-speech of the option words is compared with that of the example words, and a similarity score is calculated based on the features of the option words to select the optimal option word. This invention determines the features of the current word by extracting features from surrounding words and calculating correlation; it uses a corpus to calculate the mutual information between two words to achieve the correlation between the two words.

A computerized method of assigning a building automation system point type to a plurality of unclassified data points is provided. The method includes receiving unclassified data points and attributes for each data point. The method includes receiving classifications for a first subset of the unclassified data points. Each classification associates a data point with a building automation system point type. The method includes generating a term set containing substrings that appear in the attributes. The method includes generating a first matrix describing a frequency that the substrings appear in the attributes. The method includes calculating an indicator of a probability that the presence of the selected substring results in the data point belonging to the selected point type. The method includes assigning a point type to a second subset by finding the substring and potential point type pair having the greatest indication of probability.

This application relates to an FPGA-based full-offload regular expression matching system and method. The system includes a regular expression rule compilation unit and an FPGA full-matching unit. The regular expression rule compilation unit receives a set of regular expression rules, extracts fixed feature substrings from each rule, compiles a uniformly formatted isomorphic NFA, and constructs a mapping table between substrings and corresponding NFAs. The FPGA full-matching unit includes a parallel high-speed string matching engine array, a string-NFA mapping table module, a full regular expression data storage, a reconfigurable general-purpose NFA engine module, and a matching result output module. It performs full-offload regular expression matching on input network traffic: scanning the traffic through the engine array, filtering traffic containing fixed feature substrings to be verified and outputting substring identifiers, querying the NFA identifiers through the mapping table module, and loading the NFA for matching by the reconfigurable engine module. This method ensures low latency and high throughput performance for regular expression matching in high-speed network environments.

The application relates to the technical field of data processing, and discloses a SQL-based column segmentation method, device, equipment and storage medium, which comprises the following steps: obtaining a to-be-divided string, and sorting different text data in the to-be-divided string; saving the sorted string to a first temporary table space of a database, obtaining the number of substrings of the text data of the sorted string in the first temporary table space; dividing the text data according to the number of substrings to obtain divided text data; performing a column-to-row operation on the multiple substrings in the divided text data respectively, so that each column comprises one substring; saving the substrings and the corresponding number of times of the substrings to a second temporary table space of the database, sorting the substrings according to the corresponding number of times of the substrings to obtain a segmentation result. The application can be applied to the data processing of financial technology and medical health, can avoid increasing the complexity of a database management system, and can reduce the configuration and maintenance cost of the database.

The invention relates to a weak password judgment method and device. The method comprises the steps of obtaining a target character string, wherein the target character string is used for indicating a preset continuous character sequence and / or a keyboard character sequence; acquiring a password character string input by a user, and splitting the password character string into a plurality of substrings; a first array of each substring is determined, a second array is determined according to the first array, the first array is used for describing prefix and suffix features of a pattern string pointer on the substring, and the second array is used for indicating a rollback position of the pattern string pointer in the substring when matching fails; according to the second array of each substring, string matching is conducted on the substring and the target character string, a password judgment result is determined according to a matching result, and the password judgment result is used for indicating whether the password character string belongs to a weak password or not. According to the scheme provided by the invention, redundant and repeated operations can be reduced, and the recognition efficiency of the weak password is improved.

The embodiment of the present application discloses a kind of artificial address text similarity processing method and system filled in.This embodiment of the present application removes the regular character appearing in address in a reasonable way, so as to remove the error similarity contribution caused by address regular character.Using lower time complexity, the common substring of all more than two lengths in two addresses is calculated.A designed increasing function can map the length sequence of common substring into [0,1] space, and the function reasonably describes the characteristics of human-filled address data.A kind of address clustering algorithm capable of identifying not similar but actually identical address is designed.

The application relates to the technical field of network security, and in particular to a signature method and device, equipment and a medium. In the embodiment of the application, on the basis of obtaining a first string corresponding to request data, the first string is first divided into a first preset number of first substrings, then a shift operation is performed on each first string according to the offset corresponding to each first substring, and finally each string obtained after the shift is spliced to obtain a signature string. The complexity of the corresponding signature algorithm is higher, even if a rule-violating person with reverse experience tampers with the request data, it is impossible to think how to sign the tampered request data based on the signature algorithm of the application, therefore, the server can accurately verify whether the request data is tampered with based on whether the received signature string and the signature string calculated by the server based on the request data are consistent, and the security is higher.

The invention provides a bidding document duplicate checking method, system and device and a medium. The method comprises the steps of obtaining file content of a bidding document; the bidding document comprises a document to be subjected to duplicate checking and a comparison document; extracting sub-strings of the file content; performing bucket dividing processing on the sub-character strings, and mapping the sub-character strings meeting a preset condition into the same hash bucket; calculating the similarity between the sub-character strings of the document to be subjected to duplicate checking and the sub-character strings of the comparison document in the same hash bucket, and determining the pairing relationship between the sub-character strings; performing pairing and merging according to the pairing relationship to obtain a maximum repeated fragment; and calculating a content repetition rate according to the maximum repetition fragment so as to determine a duplicate checking result of the bidding document. Similar sub-strings are concentrated in the same hash bucket through a bucket dividing strategy, so that rapid repeated detection of large-scale text data is realized, and the duplicate checking response speed is increased; and determining the maximum duplicate fragment according to the similarity and the pairing relationship, thereby solving the problem that duplicate fragments with a small number of altered characters cannot be identified.

An adder for binary strings comprises a plurality of adder circuits arranged such that each adder circuit executes an addition of bits in the same position on a pair of binary substrings at the same t

A quantum computing task processing method includes: performing transformation processing on input quantum states of n+m qubits through a parameterized quantum circuit, the n+m qubits including n task bits and m auxiliary bits; measuring output quantum states of the n+m qubits to obtain a bit string of the n+m qubits; updating parameters of the parameterized quantum circuit based on output quantum states of the n task bits when an auxiliary substring satisfies a post-selection condition and the parameterized quantum circuit has not converged, the auxiliary substring being a substring corresponding to the m auxiliary bits in the bit string; and obtaining a computing result of the target quantum computing task based on the output quantum states of the n task bits when the auxiliary substring satisfies the post-selection condition and the circuit has converged.

An apparatus, system and method of entity / mention text transformation. The disclosure is and includes a computer readable medium storing non-transitory instructions that, when executed by a processor, cause the processor to perform operations including: recognizing entity text in an online posting comprising a plurality of substrings, wherein the plurality of substrings includes a subset of candidate strings, wherein the subset of candidate strings includes at least a first candidate string, and wherein the recognizing includes determining a first entity corresponding to the first candidate string; mapping the first entity to a first set of one or more prospective replacement texts; ranking the prospective replacement texts based on a plurality of weighted factors; and reconstructing the online posting, wherein the reconstructing includes replacing the first candidate string with a highly ranked one of the prospective replacement texts.

This invention relates to the field of document processing and text analysis technology, and discloses a text comparison method based on a sliding window and a dynamically expanding KMP algorithm. This method sets a minimum matching threshold, uses a sliding window with a step size of 1 to extract substrings from the document character by character as matching patterns, and then employs an improved KMP algorithm for scanning and matching to fully preserve the actual position information of characters in the original text. This effectively avoids positional deviations and context loss caused by preprocessing in traditional methods. After a successful initial match, the system automatically enters a dynamic expansion phase, extending the matching range character by character until continuous matching is no longer possible, thereby determining the longest repeating text segment. After matching, a dedicated result merging module intelligently merges and structures adjacent or overlapping matching segments, ultimately outputting a clear result containing the original start and end positions, repeating content, and length information. These operations significantly improve the efficiency and accuracy of large-scale document comparison.

The present disclosure provides an instruction recognition method, an instruction recognition device, an equipment and a computer medium. The instruction recognition method comprises: acquiring a to-be-recognized voice, and performing voice recognition on the to-be-recognized voice to obtain a corresponding recognized text; matching the recognized text with N command texts in a command text library to obtain N longest common subsequences and N longest common substrings of the recognized text and the N command texts; wherein N is an integer greater than 0; and determining a target text corresponding to the recognized text in the command text library according to lengths of the N longest common subsequences and lengths of the N longest common substrings.

The specification relates to the technical field of computers, in particular to a two-dimensional code check-in system, method and device and a two-dimensional code generation method. The system comprises a server, a check-in client and an attending client. The server is used to extract at least one character in a first token string corresponding to each conference scene, divide the first token string into multiple sub-strings; after determining that the check-in client and the attending client correspond to the same conference scene, analyze a first sub-string in a check-in client two-dimensional code and a second sub-string in an attending client two-dimensional code; according to a conference scene number, restore the first sub-string and the second sub-string to generate a second token string; judge whether the first token string and the second token string are consistent; the check-in client is used to generate a check-in two-dimensional code; and the attending client is used to generate an attending two-dimensional code according to a current time and a conference scene number of the attending client. The scheme enhances the security of the generated two-dimensional code and avoids false check-in by photographing and scanning the code.

A method for formatting a binary string in such a way that the need to consider a carry-over bit from an upstream adder is removed, by splitting the binary string into a pair of binary substrings and

A suspicious Uniform Resource Locator (URL) of a resource on the public Internet is detected by searching a part of the URL for a candidate substring, which is the longest possible substring that is in accordance with a Base64 encoding scheme. The candidate substring is converted to a candidate binary data in accordance with the Base64 encoding scheme. The candidate binary data is then converted to a candidate American Standard Code for Information Interchange (ASCII) string. The candidate ASCII string is evaluated to determine the information type of the candidate ASCII string. A determination as to whether the URL is suspicious is based at least on the information type of the candidate ASCII string.

Embodiments provide systems, methods, and computer storage media for determining string similarity and pattern matching in strings that arrive in a stream. A stream representing string of characters is received and used to compute mapping values that are compared to a mapping value of a query string to identify a match between strings in the stream of characters and the query string. The stream of characters is searched in a single sequential pass to detect a match or the longest matching substring with a query string. An identified match or absence of a match is provided.

The invention discloses a mixed enhanced Text-to-SQL (Structured Query Language) method based on LLM (Logistics Language Model), relates to the technical field of large language models, and particularly relates to the mixed enhanced Text-to-SQL method and device based on LLM, a dictionary-mapping mechanism adopted by the method can effectively solve the ambiguity problem of LLM to terminologies, and can reduce fuzziness of semantic matching; a three-level dynamic matching scoring algorithm can accurately distinguish a complete matching scene from a partial matching scene, and a dynamic reward mechanism improves the recognition rate of long-tail words; according to the method, verification is carried out through a keyword channel and a semantic channel, and the setting of dual-channel verification not only can improve the entity recognition speed by 50% +, but also can effectively avoid logic errors caused by purely depending on LLM (Logical Language Model); according to the method, included short substrings are removed through coverage analysis, dynamic redundancy control is achieved, repeated substring processing is avoided, 30% + invalid calculation can be reduced, and resource consumption is effectively reduced.

The application discloses a learning index construction method and device for string data and a medium, and the method comprises the following steps: acquiring first string data; dividing the first string data to obtain a plurality of first substrings; encoding the plurality of first substrings to obtain corresponding first encoded integers; searching for a corresponding index layer through layer-by-layer index searching according to a sequence number; creating an initial subnode array; inserting the first encoded integers into the initial subnode array to obtain a to-be-trained subnode array; inputting the first encoded integers in the to-be-trained subnode array into a first preset learning index model for training to obtain a first target learning index model corresponding to the to-be-trained subnode array, and the first target learning index model is used for indexing target string data. The application realizes string data indexing, improves the indexing efficiency, and reduces the space cost of the indexing structure. The application can be widely applied to the technical field of data indexing.

The invention belongs to the technical field of ship data processing, and particularly discloses a ship product structure tree node matching method and device and electronic equipment, and the method comprises the steps: carrying out the character-by-character comparison of a to-be-matched node character string with each character string in a preset node character string set, obtaining a substring inclusion relation, an LCS coincidence rate and a relative editing distance corresponding to each character string in the to-be-matched node character string and the preset node character string set; inputting the substring inclusion relation, the LCS coincidence rate and the relative editing distance corresponding to each character string in the to-be-matched node character string and the preset node character string set into a pre-trained neural network model, obtaining a comprehensive similarity score corresponding to each character string in a to-be-matched node character string output by the neural network model and each character string in a preset node character string set; and obtaining a matching result based on the comprehensive similarity score corresponding to each character string in the to-be-matched node character string and the preset node character string set.

The application provides a micro-service deployment and scheduling method and system based on an improved genetic algorithm, relates to the technical field of micro-service architecture, and encodes chromosomes based on deployment substrings and scheduling substrings; initializes a population; calculates fitness, and performs selection operation based on the combination of optimal preservation and roulette; performs two-point crossover operation based on self-adaption; performs basic bit mutation operation based on self-adaption; judges whether a termination condition is reached; if the termination condition is reached, performs catastrophe operation, so that the population iteratively evolves to a preset number of times, the individual with the highest fitness is saved, and the deployment substrings and scheduling substrings in the remaining individuals are subjected to mutation operation with a very high probability. The application establishes the deployment substrings and the scheduling substrings, the length of the deployment substrings depends on the number of resource centers and the number of micro-service types, and is much smaller than the number of tasks brought by user requests, so that the coding length of each individual is reduced, and the search efficiency is improved.

A method for remediating duplication errors associated with first and second documents includes obtaining a first document and a second document, generating a corresponding first document string set and a second document string set, generating a second document string subset that is a proper subset of the second document string set, dividing the second document string subset into second document substring, transforming the second document substrings into a synthetic substring set, converting the first document string set into first document embeddings in vector space, converting the synthetic substrings into synthetic embeddings, generate a closest embedding set of one or more first document embeddings, generating, using a respective one of the closest embedding sets and a linking string generator, a linking string defining an association between the respective substring and one or more respective first document portions, and generating a string match matrix data.

Provided herein are systems and methods for detecting and sanitizing sensitive data using domain-enhanced attention neural networks. In some embodiments, a processor of a client retrieves training data comprising tuples. Each tuple comprises a first parameter and a second parameter. For each tuple the processor matches a substring in a first parameter of the respective tuple to a keyword of a plurality of keywords, identifies a security category corresponding to the at least one keyword, and expands the first parameter of the respective tuple to comprise a respective string associated with the application event and the security category. The processor trains a model to detect and sanitize the sensitive data from the application events using the tuples, including an expanded first parameter for each tuple. The processor sanitizes the sensitive data using the trained model.

A method for remediating duplication errors associated with first and second documents includes obtaining a first document and a second document, generating a corresponding first document string set and a second document string set, generating a second document string subset that is a proper subset of the second document string set, dividing the second document string subset into second document substring, transforming the second document substrings into a synthetic substring set, converting the first document string set into first document embeddings in vector space, converting the synthetic substrings into synthetic embeddings, generate a closest embedding set of one or more first document embeddings, generating, using a respective one of the closest embedding sets and a linking string generator, a linking string defining an association between the respective substring and one or more respective first document portions, and generating a string match matrix data.

This application provides a deep learning-based regular expression matching method, apparatus, electronic device, and storage medium. The method includes acquiring a text string to be processed and segmenting it into multiple text substrings; sequentially inputting the multiple text substrings into a pre-trained prediction model to obtain the initial state prediction results output by the prediction model, the initial state prediction results including the predicted initial DFA state value of each text substring; for each text substring, performing string scanning based on the predicted initial DFA state value of the text substring to obtain the corresponding regular expression scanning result; and determining whether the concatenation condition is satisfied based on the connection relationship between the scanning results corresponding to all text substrings to obtain the regular expression scanning result of the text string to be processed.

The invention provides a file data checking method and system, a medium and electronic equipment. A table data dynamic expansion array and a paragraph data dynamic expansion array are extracted by obtaining a standard analysis file; and calling a rule base comprising charge checking calculation, a qualification name base, exclusive clause detection based on a longest common substring algorithm, a text repetition degree judgment rule, a sequential logic rule, a project grade division rule and other rules to perform comparison verification on the structured data to generate an exception report comprising a file source and exception information. According to the method and the device, automatic file checking is realized, traditional technical obstacles are overcome, and the file checking accuracy is improved.

This application provides a data query method, electronic device, computer storage medium, and program product. The method includes: using a statistical language model to segment a natural language query statement into multiple corresponding query segments; constructing a structured query language (SQL) statement for querying based on the multiple query segments using regular expressions, and obtaining multiple candidate query results by executing the SQL statement; extracting the longest common substring from each of the multiple candidate query results and the natural language query statement to obtain a target common substring; and determining the target query result that responds to the natural language query statement from the multiple candidate query results based on the target common substring. Therefore, this method can improve data query efficiency and the accuracy of query results, thereby meeting the user's query needs.