87 results about "Reverse index" patented technology

The embodiment of the invention provides a file resource reuse library management method and device based on a database, and efficient management of project resources is realized by constructing a distributed column family database cluster and dividing the distributed column family database cluster into a plurality of special column families. A multi-dimensional index mechanism is innovatively designed and comprises reverse indexing, reverse indexing and version linking, and flexible resource retrieval is supported. A distributed version lock and a transaction manager are introduced to process concurrent access, and a multi-user cooperation scene is intelligently processed through a conflict detector. And the system automatically processes resource import and tool chain configuration, so that the consistency and reliability of resource reuse are ensured. According to the method, the limitation of traditional file resource management is broken through, and an efficient resource reuse solution is provided for large-scale project development.

The invention discloses an electronic archive intelligent retrieval method and system based on a block chain, and relates to the technical field of archive retrieval, and the method comprises the steps: extracting text features of an electronic archive, and generating metadata; generating a content hash value from the electronic file original text; writing the metadata, the content hash value and the ABE access strategy into the block chain smart contract; constructing a reverse index based on the metadata semantic tag, wherein an index entry is associated with a block chain storage address; calculating a root hash and anchoring the root hash to the block chain; analyzing a keyword and a digital identity certificate in the user retrieval request; calling an intelligent contract to verify whether the user attribute accords with the ABE access strategy of the target file; retrieving an encrypted hash list matched with the file in the distributed index; acquiring the encrypted file fragments from the distributed storage system; verifying data integrity; and combining the fragments to generate a final retrieval result. The method has the advantages that through deep coupling of the block chain and attribute encryption, an electronic archive management system considering security and intelligent retrieval is constructed.

The invention provides a medical AI question and answer method based on retrieval enhancement, which comprises the following steps: acquiring a medical professional knowledge base, and constructing an entity recognition model and a medical knowledge graph; the method comprises the following steps: splitting a medical professional knowledge base, and creating a vector index and a full-text retrieval reverse index; intention classification is carried out, and initial processing is completed; performing multi-path mixed retrieval on the medical professional knowledge base to obtain a user question related text block; a filtering rule is preset, and the user question related text blocks are filtered; answering the user question according to a preset second prompt word, and answering the user question according to a preset third prompt word when the user question exceeds the range of the medical professional knowledge base or the multi-path mixed retrieval has no result. According to the method, related context information can be accurately searched, reliable reference information is provided for a generative large model to answer professional questions, the interactive experience of a medical question answering system is improved, and the accuracy and specialty of answer generation of the system are remarkably improved.

The invention discloses a progressive topic generation method based on semantic analysis and a knowledge graph. Performing preprocessing and semantic analysis on the question setting demand text, and extracting a necessary keyword set corresponding to the core knowledge points and an optional determiner set corresponding to the additional conditions; carrying out concept mapping in a college professional knowledge graph and associating with a course outline, constructing a hierarchical semantic constraint framework containing hard constraint and soft constraint, and carrying out consistency detection; adopting reverse index hard matching recall and knowledge graph soft extension recall to obtain candidate materials, and inputting the candidate materials into a field fine-tuning large language model to generate candidate questions; reordering is performed through multi-target learning ordering, teaching logic verification and quality evaluation are executed, and final questions are output; user feedback is received to form an incremental sample, and the generation model and the sorting model are updated, so that the accuracy, diversity and controllability of question generation are improved, and closed-loop optimization is supported.

The invention discloses a standard address pipeline data association management method and system based on multi-level collaborative coding, belongs to the technical field of government affair digitization, and aims to solve the technical problem of how to generate and manage standard address data in government affair business, realize automatic triggering and standardized circulation of cross-department business data and improve the management efficiency. According to the technical scheme, the method comprises the steps of cross-department business triggering: automatically triggering a road and courtyard address code generation process through construction project land pre-examination and construction project planning permission business events; a standard road name is generated based on road pre-examination data, a road unified identification code is synthesized according to a 4 + 6 + 9 segmentation rule, a house number is generated according to planning permission data, and a courtyard unified identification code is generated in combination with a naming system; the house prediction data triggers the generation of a house unified identification code; and data dynamic association: constructing a reverse index based on the address coding feature vector, and realizing millisecond-level accurate matching of the address and population information through a distributed query engine.

The invention discloses an enterprise knowledge base retrieval and intelligent answering method and system based on a large language model. The method comprises the following steps: performing clause-level segmentation on an enterprise knowledge base document, associating document metadata to form structured knowledge entries, and establishing a keyword reverse index and a semantic vector index for the structured knowledge entries; analyzing the natural language query of the user, and performing multi-strategy expansion to generate an enhanced query expression and a query semantic vector; performing dual-channel mixed retrieval, performing duplicate removal, version filtering and weighted fusion sorting on a result, and generating a final candidate knowledge item list; and based on the candidate list and a predefined instruction, calling a large language model to generate a structured answer with complete traceability information. The method is compatible with an existing retrieval framework, precise understanding, knowledge point-level positioning, cross-document content integration and version consistency control of natural language problems are achieved, and the retrieval accuracy, answer availability and service intelligence level of an enterprise knowledge base are remarkably improved.

A computer-implemented method for performing searches in a document database is disclosed. The method comprises automatically detecting a line of business associated with a user, receiving a text query from the user, and generating a query embedding from the text query. The method further comprises scoring entries in a reverse index using a hybrid scoring function. The reverse index comprises titles, title embeddings, sentences, sentence embeddings, and entity tags corresponding to documents in the document database. The hybrid scoring function is used to generate a score based both on a keyword match score between the text query and the reverse index and on a cosine similarity score calculated from embeddings in the text query and in the reverse index. The method also comprises ranking scores for sentences in the document database, and displaying a sentence associated with a top score to the user.

The invention discloses a video retrieval generation method and device based on sparse representation and reordering, and relates to the technical field of cross-modal video retrieval. The method comprises the following steps: acquiring a query text, a candidate video sequence and a video retrieval generation model; obtaining a query text dense representation and a candidate video sequence dense representation according to the encoder module, the query text and the candidate video sequence; through a sparse representation module, text sparse representation is generated according to the query text dense representation, candidate video sparse representation is generated according to the candidate video sequence dense representation, and reverse index screening is performed on the candidate video sequence to obtain part of candidate videos; determining a global score of each video in the partial candidate videos through a cross attention module, and sorting the partial candidate videos; and through a generation module, generating a target text corresponding to the query text according to the sorted candidate videos and the query text. By adopting the method and the device, the retrieval efficiency is improved in a sparse representation and reordering mode.

The invention discloses a voice data compression and index storage method based on a voiceprint template, and relates to the technical field of voice compression processing. The voice data compression and index storage method based on the voiceprint template comprises the following steps: S1, collecting and preprocessing acoustic state data, coded data and edge synchronization data, and constructing a standardized voice input data set; s2, evaluating the individual sound channel difference degree, and stripping non-universal components highly related to individuals in the voice; s3, analyzing the audio compression content, and constructing a structured total compression amount; s4, performing joint evaluation on real-time transmission regulation and control requirements of the compressed data, and dynamically adjusting an uploading priority and a continuous transmission strategy; and S5, constructing a multi-dimensional reverse index system at the cloud. The problems that for a high-noise far-field pickup scene, an existing compression method does not consider that individual sound channel characteristics are stripped from original signals, so that compression redundancy is high, and retrieval interference is large are solved.

The invention discloses a code adoption rate determination method and device, equipment, a storage medium and a product, and relates to the technical field of software development, the code adoption rate determination method comprises the steps that a code line information base comprising a first code is constructed, and a reverse index corresponding to the first code is constructed based on the code line information base, the first code comprises one of the following: an auxiliary code generated by a large language model, and a new code of a target code warehouse within a target time period after the auxiliary code is generated by the large language model; and matching a second code with the first code through the code line information base and the reverse index to determine the code adoption rate corresponding to the auxiliary code. Therefore, the technical problem that the actual contribution of the large language model in the software development process is difficult to quantitatively evaluate can be solved, and the technical effect of determining the actual contribution of the large language model based on the code adoption rate is achieved.

The invention discloses a policy question and answer system based on a large language model, a reverse index and embedded retrieval. The policy question and answer system comprises a data preprocessing module, a reverse index module, an embedded retrieval module, a retrieval management module, a question and answer generation module and a user interface module. Relates to the technical field of policy questioning and answering, and solves the technical problem that an existing policy questioning and answering system often cannot give consideration to retrieval efficiency and semantic understanding at the same time, so that the accuracy and correlation of answers are insufficient. Through a two-stage retrieval mechanism combining reverse indexing and embedded retrieval, firstly, candidate policy texts are quickly screened out through reverse indexing, then, a plurality of policy texts and demand problems are converted into two high-dimensional vectors and are compared, fine sorting is performed according to comparison results, and the policy texts and demand problems are accurately sorted. And the candidate policy texts which are finely sorted by the large language model are taken as references for answering, so that the correlation and accuracy of retrieval results can be improved.

The invention discloses a method and a system for realizing compatible file hard link and S3 shallow copy based on a distributed key-value pair, a file metadata key-value pair is used as a metadata storage main body of a file or a directory, a key consists of a file system ID (Identity), a parent directory ID and a file or directory name, and a value contains metadata information; a reverse index file handle key value pair is introduced to serve as a unique invariant identifier, a key is composed of a file system ID, an initial parent directory ID, an initial file or first N characters of a directory name and a file ID, and a value contains a current file metadata key and a reference count. When files or directories are created and deleted, the files or the directories are located at the same one-key value pair node in a large probability, and one-stage submission is supported to improve performance; hard linking and S3 shallow copying are achieved at the same time, independent file metadata key-value pairs and reverse index file handle key-value pairs are created for the hard linking and the S3 shallow copying, reverse index file handle keys of the target file are recorded by file metadata values of the file metadata key-value pairs, reference counts of the reverse index file handle values of the target file are updated, and performance and compatibility are both considered.

The embodiment of the invention provides a search method and related equipment / products, and relates to the technical field of Internet. The search method comprises the following steps: receiving a search request sent by a client, wherein the search request carries an identifier of a target object; determining a target index entry from a plurality of index entries of an object reverse index based on the identifier of the target object; the object reverse index is constructed based on video contents of a plurality of live broadcasting rooms, the video contents correspond to one or more objects, and each index entry corresponds to one object and indicates an identifier of the live broadcasting room associated with the object; determining an identifier of a target live broadcast room associated with the target object according to the target index entry; and generating a target live broadcast room list according to the identifier of the target live broadcast room, and pushing the target live broadcast room list to the client. According to the technical scheme, a more visual, accurate and comprehensive search result can be provided, so that the search experience and the platform competitiveness are effectively improved.

The technical scheme of the invention provides a performance optimization system for real-time memory retrieval based on an inverted index. After the technical scheme disclosed by the invention is adopted, the average response time of an interface is less than 10ms under the condition of multi-field combined query (OR and AND) under the condition of 1 billion data volume in a high-frequency write operation service. According to the query optimization system based on the memory inverted index technology disclosed by the invention, the efficient inverted index structure is constructed in the memory, and the AND and OR operations between the fields are accelerated by utilizing the structure, so that the complex query performance of a large table is remarkably improved. The query efficiency is remarkably improved; the expandability of the system is enhanced; and user experience is improved.

The invention discloses a method and device for extracting concerned phrases in a text, a storage medium and equipment, and belongs to the technical field of computers. The method comprises the following steps: acquiring a reverse index and a multimode matching model which are constructed for concerned phrases; detecting an input text by utilizing the multi-mode matching model to obtain a plurality of fragments; collecting the plurality of fragments by using an inverted index to obtain a first fragment set; segmenting the first fragment set according to a preset editing distance to obtain multiple groups of second fragment sets; for each group of second fragment sets, screening candidate fragments according to editing distances between fragments in the second fragment sets and the concerned phrases; and combining the candidate fragments in each group of the second fragment sets into similar variants of the concerned phrases, and identifying the similar variants of which the editing distances to the concerned phrases are greater than a predetermined threshold value as the concerned phrases. According to the method, the similar variants of the concerned phrases in the text can be identified as the concerned phrases by utilizing the improved multi-mode detection model and the inverted index, so that the extraction accuracy is improved.

The invention discloses a graph similarity search method based on sub-graph matching, which comprises the following steps of: dividing a data graph into a plurality of mutually exclusive half-edge graphs, constructing a reverse index by taking sub-graph embedding as a key and a data graph set containing the sub-graph as a value, constructing a coordinate index based on size information of the data graph, and realizing hierarchical filtering by utilizing a mapping relationship between two layers of indexes. A self-loop or loop-free strategy is adopted to process half sides, a sequential embedding model is designed, so that embedding of two graphs with a sub-graph isomorphic relation in a high-dimensional space has the same partial sequence position, a query graph is input, a preliminary candidate set is screened out through coordinate indexes, then the candidate set is further screened out through inverted indexes, and a final candidate set is obtained; the graph editing distance between the query graph and the candidate graph is accurately calculated, a final result set is obtained, traditional sub-graph isomorphism testing is avoided, sub-graph embedding can be generated in the off-line stage, and the deduction time of the model is greatly shortened.

A transaction log query processing method and a storage node, the storage node storing a plurality of transaction logs through a plurality of log blocks, the method comprising: receiving a data query request indicating a first field and a corresponding first field value, the first field being a discrete field; querying a bitmap index corresponding to the first field to obtain an existence bitmap corresponding to the first field value; determining a target log block from the plurality of log blocks according to the existence bitmap; querying a reverse index corresponding to the first field in the target log block, and determining a target transaction number corresponding to a target transaction log involving the first field and the first field value in the target log block; and according to the target transaction number, reading the target transaction information from the target transaction log.

The invention provides a retrieval method for a large language model and a multi-modal model, electronic equipment and a medium. The method comprises the steps of performing first preprocessing on a knowledge base to obtain a vector database; performing second preprocessing on the knowledge base to obtain a reverse index database; obtaining a search word; performing third preprocessing on the search word to obtain a first search word set, performing retrieval by a vector database according to the first search word set, and obtaining a vector recall slice set according to the vector database; performing fourth preprocessing on the search word to obtain a second search word set, performing retrieval by a reverse index database according to the second search word set, and recalling a text slice set according to feedback of the reverse index database; and receiving the vector recall slice set and the text slice set, combining the vector recall slice set and the text slice set into a recall slice set, processing the recall slice set, and inputting the processed recall slice set into a large language model to obtain a retrieval result. Therefore, the retrieval result provided by the invention is more accurate.

The invention discloses an NL2SQL method, device and equipment based on a preset industry large model and a medium, and relates to the technical field of computers, and the method comprises the steps that attribute names and attribute data types are extracted from table data in a database, and a value index and a reverse index are determined based on an attribute extraction result; when query information is received, the query information is preprocessed based on a preset industry large model, and full-text retrieval is carried out by utilizing a preprocessing result and the reverse index; performing dynamic mode generation through a preset industry large model, the full-text retrieval result and an intention recognition result corresponding to query information determined based on the preset industry large model, and feeding back an obtained target query mode to the client; and when it is determined that the query mode correction triggering condition is not met currently based on the received client reply information, determining a target SQL statement based on a preset industry large model, the query information and the target query mode. According to the method, the accuracy and the reliability of generating the SQL statement can be effectively improved.

The invention provides a data discovery method, system and device based on weight distribution and entity annotation and a medium, and belongs to the technical field of data search processing. Dynamically adjusting the weight of each data item by adopting a machine learning algorithm according to the actual characteristics of the data; a self-adaptive weight distribution model is configured, and actual features in the data are labeled in a multi-layer entity labeling mode; constructing a reverse index retrieval model, extracting features of each data item according to the self-adaptive weight distribution model, distributing corresponding weights, performing score calculation, performing sorting according to scores, and feeding back to users; a closed loop is formed by collecting and analyzing user search data, dynamically adjusting adaptive weight distribution, a search and sorting algorithm and an index performance optimization strategy, iteratively executing evaluation and optimization and combining a user feedback mechanism. The method can accurately reflect the importance of different features to search results. And diversified search requirements of the user can be better met.

The invention relates to a network authentication method and device based on ISTIO and OPA, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: deploying a service agent Envoy and an OPA Agent in a sidecar mode in a minimum deployment unit Pod containing the OPA; the method comprises the following steps of: configuring an Istio, generating a Service Entry resource and an Extension Provider resource, and opening a service port of an OPA (Open Power Area); the method comprises the following steps of: customizing the content and the effective range of an authentication strategy of the OPA by configuring an OPA Policy resource; synchronizing the authentication strategy to a corresponding Pod in a multi-cluster environment by using a synchronous compensation mechanism; constructing a reverse index, and mapping the label of each authentication strategy to a resource list with the corresponding label; and under the condition that the resource with the preset tag needs to be searched, querying the reverse index to obtain a corresponding resource list. By adopting the method, the network authentication process is more efficient, flexible and easy to manage through automatic management and calculation, distribution and retrieval of the optimization strategy.

Example methods and systems are directed to reverse indexing. According to some examples, a reverse index is generated based on source data and a ranking list threshold. The reverse index includes one or more restricted emission lists. Each restricted emissions list has a maximum size corresponding to an emissions list threshold. The method may include receiving a search query including a value identifying a restricted emission list of the one or more restricted emission lists. The value may be used to retrieve and return one or more record identifiers from the identified restricted emissions list. The record identifier uniquely identifies one of a plurality of records in the source data.

This invention discloses a method and system for extracting meta-analysis literature based on graph-anchored multi-agent systems. The method includes reconstructing unstructured PDFs into a hierarchical semantic document structure through visual document analysis and identifying functional area labels; applying functional area anchoring constraints to limit information search to specified functional area nodes; scheduling a multi-agent collaborative extraction network consisting of a reconnaissance agent, a logic assembly agent, and an indicator retrieval agent; and completing experimental variable identification, logical mapping between treatment and control groups, and cross-paragraph indicator retrieval through structured message dialogue and multi-round collaboration; employing a neural symbolic hybrid engine, where semantics are parsed by a large language model and precise mathematical aggregation operations and dimensional conversions are performed by a deterministic symbolic computation engine; and generating a structured data matrix with inverted index pointers. This application achieves high-precision, zero-error, and traceable automated extraction of meta-analysis literature data.

Rather than collecting flow logs at a central location, and then processing these flow logs to create general purpose or specialized data stores, the embodiments herein rely on the network appliances to create the flow logs and metadata that indexes these flow logs. The flow logs and the metadata can then be collected at the central location (e.g., a central analyzer) and merged with flow logs and metadata generated by other network appliances to yield a data store that can be used to analyze the flow logs in computing environment (e.g., a data center).

The present invention discloses a short text stream clustering method based on episodic memory, which relates to the field of text data mining. Short text streams have characteristics such as infinite length, topic evolution, and sparse text features. Most of the existing short text stream clustering methods based on similarity require manual setting of a similarity threshold and cannot handle the text sparsity problem well. The present invention proposes a short text stream clustering method based on similarity of episodic memory. First, the idea of episodic memory is incorporated into the stream clustering algorithm. Then, the feature representation of clustering is enhanced through sparse experience replay, and the reverse index is used to improve the clustering efficiency. In the online stage, through a new similarity calculation formula and dynamic calculation of the similarity threshold, the current text is assigned to an existing cluster or a new cluster, and the clustering features are continuously updated. In the offline stage, the overall algorithm performance is improved through a clustering enhancement algorithm, a semantic reallocation algorithm, and an algorithm for deleting outdated clusters.

The invention provides a vector query method of a vector database and a related product. The method comprises a step of constructing a reverse index and a step of carrying out vector query based on the reverse index. In the step of establishing the reverse index, preprocessing each data vector to reduce the dimension of each data vector, and then clustering; in the vector query step based on the inverted index, the vector to be queried is preprocessed to reduce the dimension of the vector to be queried, and then the neighbor node of the vector to be queried is obtained. And finally, restoring the vector to be queried and each neighbor vector, and sorting each neighbor vector according to the distance between the vector to be queried and each neighbor vector. According to the technical scheme, the vector query accuracy of the vector database can be improved.

The present invention provides a method and system for optimizing reverse indexing in a relational database. The method reduces unnecessary comparison operations in intersections by using an inverted index posting list, uses a skip merge join method to skip rows through an aggregation function provided by the database, and then uses a multi-way join method to improve join performance and shorten the query process by simplifying complex join methods, so as to obtain the result of the posting list of keywords to be searched in one process, and at the same time process the joins of multiple posting lists to be searched, without obtaining the intermediate result value of the posting list intersection, thereby shortening the search time and improving the processing efficiency.

The invention relates to the technical field of rail transit vehicle dynamics and intelligent suspension control, in particular to a high-speed train rotating arm node reverse dynamics design method based on dynamic requirements, which comprises the following steps: S1, constructing a mapping relation between vehicle dynamics performance and node rigidity, the method comprises the steps of S1, establishing a mapping relation between node rigidity and a magneto-sensitive elastomer material and structure, S3, establishing a magneto-sensitive elastomer node database, S4, carrying out reverse design based on a dynamic demand matrix, and S5, carrying out semi-active rigidity regulation and hardware-in-the-loop verification based on a controllable magnetic field. According to the invention, material and structure design parameters of the damping element can be deduced reversely, a multi-dimensional parameter database can be established, computable performance reverse indexing can be realized, a simulation-test-database self-learning mechanism is formed by combining a mechanical model and a test, and a closed-loop verification platform is constructed between a whole vehicle simulation model and a rack system. And engineering landing of the design method is realized.

The invention belongs to the field of aerospace numerical simulation, and relates to a high-quality surface grid generation method based on a local calculation method. The method comprises the following steps: firstly, processing a geometric model to obtain discrete line segments of a directed boundary of the geometric model, and then generating a grid inwards based on the discrete line segments; establishing a spatial local area, and calculating on the basis of the spatial local area, so that all calculations are concentrated in the spatial local area; the use of a local mapping domain ensures that the approximate intersection judgment of triangles in the space can be judged, and alpha, beta and gamma coefficient correction is assisted to enhance the robustness of the method, so that the high quality of the generated grid is ensured; when a to-be-generated edge is written, reverse indexing from the point ID to the edge ID is carried out by using a hash function, so that a large amount of set traversal operation is avoided, and high efficiency is realized. The method provides a basis for high-precision algorithm engineering application of computational fluid mechanics and computational electromagnetism in the fields of automobile manufacturing, ship industry, aviation industry and the like.

The invention discloses a compressed XML database type, system and method supporting efficient query, and relates to the technical field of XML databases, and the database type adopts a hierarchical compression storage architecture and a reverse search query architecture; in the storage stage, XML non-keyword information is coded through Huffman coding, recoverable ordered arrangement is carried out on the coded information through a tree structure, then transcoding is carried out, the information is stored in a disk in a binary form, and compared with a traditional XML database storage mode, at least 50% of storage space is saved. In the query stage, a reverse search mode is adopted, a corresponding Huffman code initial position is positioned through a keyword, then under the optimization effect of a reverse index, reverse search is performed to recover a complete XML structure, and the query complexity is reduced from traditional O (n) to O (1). According to the method, the storage efficiency and the query performance of the XML data are greatly improved, and the method is suitable for large-scale XML data management and application scenes.