74results about "Semi-structured data querying" patented technology

The invention relates to the technical field of data management, and discloses a file compliance detection tool, a use method, equipment, a medium and a product, the tool comprises a scanning engine, an analysis engine, a security policy library and a service database; the scanning engine is used for obtaining a to-be-detected file in an OOXML format and calling the software development suite configured based on an OOXML protocol to scan the to-be-detected file to obtain to-be-detected text content in the to-be-detected file; the security policy library is used for storing a sensitive word dictionary and a security detection rule library; the analysis engine is used for carrying out matching on the to-be-detected text content according to the sensitive words recorded in the sensitive word dictionary to obtain to-be-detected sensitive words, carrying out risk analysis on the to-be-detected sensitive words by utilizing the security detection rule base, and generating a file compliance detection report; and the business database is used for storing the file compliance detection report and the to-be-detected text content. According to the invention, the capability of quickly checking the file compliance in the intranet environment is realized.

The invention provides a test case generation method and device, and relates to the technical field of software testing, the method comprises: obtaining training data, the training data comprising a plurality of xml files, each of the plurality of xml files comprising a plurality of UI elements, attributes of the plurality of UI elements, and test operations corresponding to the attributes of the plurality of UI elements; training a test case model according to the training data; obtaining a first xml file of the first Android application under the first interface; inputting the first xml file into the test case model to determine a first test operation corresponding to a first UI element in the first xml file; and generating a test case corresponding to the first Android application based on the first test operation. Based on the test case model, the test operation corresponding to the UI element in the input xml file can be generated, the test case corresponding to the Android application is automatically generated, and the test efficiency and accuracy are improved.

The present disclosure provides a character recognition model training method and apparatus, a character recognition method and apparatus, a device and a medium, relating to the technical field of artificial intelligence, and specifically to the technical fields of deep learning, image processing and computer vision, which can be applied to scenarios such as character detection and recognition technology. The specific implementing solution is: partitioning an untagged training sample into at least two sub-sample images; dividing the at least two sub-sample images into a first training set and a second training set; where the first training set includes a first sub-sample image with a visible attribute, and the second training set includes a second sub-sample image with an invisible attribute; performing self-supervised training on a to-be-trained encoder by taking the second training set as a tag of the first training set, to obtain a target encoder.

Case management systems and techniques are disclosed. In various embodiments, for each of a plurality of case nodes comprising a case model a trait definition comprising a corresponding set of traits associated with that case node is received. The respective trait definitions are used to bind each set of traits to the case node with which the set of traits is associated in case instances created based on the case model.

Taxonomy driven multi-system networking and content delivery systems and methods are provided herein. An example systems includes a website authoring platform generating a taxonomy structure for a webpage, the taxonomy structure indicating assets to be included in the webpage a layout for the assets, a technical documentation authoring system for creating technical documents related to the assets, and a metadata binder providing the technical documentation authoring system with access to the taxonomy structure of the website authoring platform so that technical document authors are provided with the taxonomy structure to guide creation and structuring of the technical documents so that the technical documents comprise data that corresponds to the assets.

The invention discloses a cognitive resident node recognition and attention link construction method, device and system, and belongs to the technical field of user behavior modeling, and the method comprises the steps: user behavior data collection, structured processing and preprocessing; behavior chain construction and semantic alignment: unifying behavior semantic description and constructing a time sequence mapping chain by identifying a behavior stage, and providing path input for cognitive resident node identification and attention link construction; recognizing cognitive resident nodes and constructing attention links, recognizing cognitive resident points of a user in corresponding stages, and establishing flow paths of attention between different nodes and behavior stages to form a structured attention link map. The user behavior modeling method solves the problems of data dimension splitting, behavior chain missing, rough intention modeling and insufficient time sequence evolution characteristic mining in an existing user behavior modeling method.

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for performing operations comprising: receiving an image from a client device; applying a machine learning model to the image to generate an embedding query vector, the machine learning model being trained to encode a plurality of images and text into a common embedding space; searching, based on the embedding query vector, a database of augmented reality (AR) experiences to identify a subset of AR experiences associated with one or more embeddings that correspond to the embedding query vector; and transmitting to the client device the subset of AR experiences associated with the one or more embeddings that correspond to the embedding query vector.

This search system comprises an acquisition unit, a relevance degree estimation unit, a determination unit, and an output unit. The acquisition unit acquires a query. The relevance degree estimation unit estimates the degree of relevance between the acquired query and the sentence of an answer candidate included in a document having a hierarchical structure. The determination unit determines question text for narrowing down answer candidates for the query on the basis of the hierarchical structure of the document and the estimated degree of relevance. The output unit outputs the determined question text . Accordingly, it is possible to efficiently search for information requested by a user, and thus this search system can be used for assisting in decision making, for example. The search system also has a function as an optimization AI that optimizes a question for use in narrowing down answer candidates according to the situation of a user.

Examples may create input data for a causal machine learning model using pathogenicity evidence data associated with a genetic variant and a health condition. Examples may apply a causal machine learning model to the input data to produce a trained causal model. A graphical representation of the trained causal model may include nodes connected via acyclic directed edges. A first node of the nodes may represent a pathogenicity evidence variable related to the health condition. At least one second node may represent a cause of the pathogenicity evidence variable. At least one third node may represent an effect of the pathogenicity evidence variable. An acyclic directed edge may represent a relationship between two of the nodes. Examples may output predictive data sampled from the trained causal model.

The invention discloses an index operation method and device, a computing device cluster and a storage medium, and the method comprises the following steps: firstly, a key value database receives a first index operation command, the first index operation command comprises an index name of a target index and a first index operation type, and then the index operation type of the target index is determined according to the first index operation command; and executing the operation of the first index operation type on the target index. Wherein the target index comprises a target primary key index and / or a target secondary index, the target primary key index comprises a target primary key and target data corresponding to the target primary key, the target secondary index comprises a target secondary index key and the target primary key, and the target secondary index is used for the key value database to obtain the target primary key; and obtaining target data corresponding to the target primary key based on the target primary key. According to the scheme, the user is supported to specify the index to operate, and the operation efficiency and the user experience of the key value database are improved.

The invention discloses a marketing operation and maintenance abnormity positioning system based on business and technical index fusion. A configuration information acquisition module is used for establishing a mapping association basis of business indexes and technical indexes; the index data acquisition module is used for acquiring technical architecture operation indexes and business process key node indexes in parallel based on the mapping association basis established by the configuration information acquisition module to form a fusion type index data set and storing the fusion type index data set to a monitoring database; the monitoring display module is used for calling the fusion type index data set in the monitoring database, and displaying the dynamic association relationship between the business indexes and the corresponding technical indexes in a linkage manner through the same view; the alarm module performs linkage verification based on the association relationship displayed by the monitoring display module, triggers an alarm and pushes the alarm to related personnel; the anomaly positioning module is used for performing traceability analysis on the associated indexes in the fusion type index data set and positioning the source corresponding to the anomaly; according to the invention, the problems of weak association, difficult analysis, slow positioning and the like caused by service and index separation in the prior art can be solved.

The invention provides a display end, storage end and export end conversion method suitable for table data. According to the method, xml format table data of a specific structure serves as back-end data, back-end table data of the xml format is generated and analyzed through a specific method, front-end table data of a software interface or export-end table data in an external path can be converted into the back-end data, and the back-end data is stored in a database for later use; and the back-end data can also be converted into export-end or front-end table data, so that the data is exported to an external path or displayed on a software interface. According to the method, the table data of any different styles and sizes can be displayed, stored, exported and the like, and storage, display and export methods do not need to be specially designed for tables of different shapes and styles, so that the software development efficiency and the later modification and maintenance efficiency of the tables of various styles are greatly improved; and checking, editing and exporting of historical table data can be greatly facilitated.

Among other things, we describe a method of receiving a portion of metadata from a data source, the portion of metadata describing nodes and edges; generating instances of a data structure representing the portion of metadata, at least one instance of the data structure including an identification value that identifies a corresponding node, one or more property values representing respective properties of the corresponding node, and one or more pointers to respective identification values, each pointer representing an edge associated with a node identified by the corresponding respective identification value; storing the instances of the data structure in random access memory; receiving a query that includes an identification of at least one particular element of data; and using at least one instance of the data structure to cause a display of a computer system to display a representation of lineage of the particular element of data.

Examples may use pathogenicity evidence data associated with genetic variants and health conditions to create input data for a causal machine learning model. Examples may apply a causal machine learning model to input data to produce a trained causal model. A graphical representation of the trained causal model may include nodes connected via acyclic directed edges. A first node of the nodes may represent a pathogenic evidence variable associated with the health condition. The at least one second node may represent a cause of the pathogenic evidence variable. The at least one third node may represent the impact of the pathogenic evidence variable. The non-cyclic directed edge may represent a relationship between two nodes. Examples may output prediction data sampled from the trained causal model.

To provide a document retrieval apparatus, a document retrieval method and a document retrieval program, in document retrieval using retrieval keywords, which can provide the candidates of suitable retrieval keywords.SOLUTION: A document retrieval program according to an embodiment causes a computer to realize a document retrieval function, a word group creation function and a word group selection function. The document retrieval function retrieves a document related to a retrieval text inputted by a user in a document database stored with plural documents. The word group creation function creates plural word groups which classify suggested words extracted from the retrieved document using information about a document structure or classification information based on the meaning of words. The word group selection function selects the word group to be provided to the user from among the plural word groups.SELECTED DRAWING: Figure 2

The invention discloses a quality risk management method and system based on a white spirit enterprise, and relates to the technical field of risk prediction. Comprising the steps of 1, creating a quality risk management system based on a white spirit enterprise, 2, collecting, verifying and storing risk data through a risk data collection module, 3, designing, managing and calling a risk identification template through a risk identification template management module, and 4, managing and calling the risk identification template. The method comprises the steps of 1, managing risk identification, processing and tracking through a management risk identification and processing module, 2, carrying out risk analysis, assessment, grade evaluation and potential risk mining through a risk analysis and assessment module, and 3, carrying out risk information auditing, publishing, tracking and reminding through a risk publishing and tracking module. And 7, through summarization and analysis of risk data, report generation and visual display of a quality analysis module, a complete risk management and control process is formed, and it is guaranteed that risk management and control are efficient and orderly.

The invention discloses a method for storing and recovering train number, train unit number and dispatching number in a CTC station graph during construction, a readable storage medium and electronic equipment, and the method comprises the steps: S1, before construction, STPC stores the train number in an in-station train number window on a station graph interface, and the train unit number and dispatching number information on a turnout, a station track and a turnout-free section; the attribute information and the information of the equipment are synchronously stored; s2, after construction, the STPC reads the stored train number information, the stored train group number information, the stored dispatching number information, the stored attribute information and the stored equipment information, arranges and displays the stored train number information, the stored train group number information, the stored dispatching number information, the corresponding attribute information and the stored equipment information, and selects the train number information, the train group number information, the dispatching number information and the corresponding attribute information which need to be recovered based on a preset mode; and S3, based on the selection result of the S2, sending the corresponding train number, train group number and debugging number information and the attributes and equipment information thereof to the LIRC, and recovering the display of the corresponding information on the station yard graph interface by the LIRC. The method has the advantage that the operation and maintenance efficiency is effectively improved.

The present invention relates to the field of smart agricultural planting technology, and provides a smart agricultural planting management method and system. By acquiring monitoring data of a planting area, a planting database is established. Targeted storage data is acquired from the planting database through retrieval analysis, and the data is substituted into a preset training model to acquire initial control parameters and later control parameters corresponding to the plants before and after they emerge from the soil, respectively. Then, target parameters that best fit the real-time state of the current plants can be acquired, and then, by comparing with the real-time monitoring data of the planted plants, it is determined whether the planting parameters need to be regulated. Based on the database, the most suitable planting parameters are acquired through big data analysis and calculation in the cloud, which can effectively improve the level of intelligent agricultural planting, and thus meet the needs of open-air planting.

A system is disclosed, comprising a processor configured to: run a digital twin of a real-world asset; receiving a data set from a data source via a first application programming interface (API), the data source communicatively coupled to a processor; updating the digital twin based on the received data set; receiving, via a second API, a query from a user device to obtain information from the digital twin, the user device communicatively coupled to the processor; processing the query to generate a response including the information; and sending the response to the user equipment.

A structured document storage format is provided in which tokens used for encoding and decoding are contained within the encoded document in an inline dictionary. Each document is encoded independently, and there is no central dependency or any dependency on other documents during DML and query execution. Each encoded document has all information with it on disk so that the document can be independently shared, decoded, or distributed. A mechanism is provided for quickly determining a mapping between tags and tokens without having to scan the entire inline token dictionary for each document. This allows the database system to process multiple documents, each having its own inline token dictionary, without having to fully scan the inline dictionary of every document for each tag that referenced in an operation.

The invention discloses a deserialization utilization chain mining method for Dotnet, and belongs to the technical field of Web security. In order to solve the problems that an existing. NET environment is lack of a high-adaptability white-box analysis tool and automatic judgment of a deserialization utilization chain is difficult, C # source codes are generated through a decompilation program set, a code attribute graph oriented to a hosting environment is constructed, Source and Sink rules are customized, a potential vulnerability utilization chain is queried in a graph database, and the potential vulnerability utilization chain is queried in the graph database. And the validity is judged by using a large language model. According to the method, the deserialization vulnerability utilization chain in the hosting program set can be efficiently found, and the automation and intelligence level of vulnerability mining is improved.

To properly respond to a user speech in a case where the knowledge-based scale is enlarged.SOLUTION: An information processing apparatus according to the present disclosure includes: a knowledge object generation unit for extracting a plurality of terms from a text document and generating a knowledge graph indicating relationships between the extracted plurality of terms; an acquisition unit for acquiring context information in which general documents are included as knowledge; and an inference unit for generating a response sentence on the basis of a question sentence from a user and the context information.SELECTED DRAWING: Figure 1

The embodiment of the invention provides a software system reconstruction method and device, equipment and a medium, and is applied to a compiler, the method comprises the following steps: in a software system reconstruction process, in response to a reconstruction instruction for a software system, obtaining a source code directory of the software system; compiling the source code directory to generate a corresponding abstract syntax tree, and extracting matching information related to a reconstruction target from the abstract syntax tree; obtaining an initial shadow catalogue of the source code catalogue, reconstructing the source code catalogue according to the initial shadow catalogue and the extracted matching information, and generating a target shadow catalogue; and finally, replacing the source code catalog with the target shadow catalog, completing reconstruction of the software system, obtaining a reconstructed target software system, automatically reconstructing the software system through a compiler, generating matching information accurately matched with a reconstruction target by utilizing an abstract syntax tree, and automatically and efficiently reconstructing the software system in combination with a shadow catalog mechanism. And the accuracy and safety of the reconstruction process are ensured.

The present invention provides a method and system for managing the operation, distribution, and dispatching model, including: searching for the distribution automation model to obtain the boundary devices of the dispatching model, the distribution automation model, and the marketing model; analyzing the boundary devices to obtain the overlapping device information and topological information among the distribution automation model, the marketing model, and the dispatching model; respectively processing the overlapping device information and topological information in the distribution automation model, the marketing model, and the dispatching model, and merging the distribution automation model, the marketing model, and the dispatching model to obtain the integrated operation, distribution, and dispatching model. The present invention can solve problems such as overlapping device information and blurred boundaries between operation and distribution, and between dispatching and distribution, realizes the effective management of boundary devices and the integration of the operation, distribution, and dispatching model based on the boundary devices, can provide an integrated operation, distribution, and dispatching model for the integrated power supply service command platform, and provide data support for the lean management of the distribution network operation and maintenance, the continuous improvement of power supply reliability, and the improvement of power supply service level.

Case management systems and techniques are disclosed. In various embodiments, searching case instances is facilitated. An indication to create a composite index across hierarchical case nodes comprising a case model is received. Case instance data associated with the case model is used to generate the composite index. The composite index is made available to be used to optimize searches of a plurality of case instances with which the case instance data is associated.

The invention relates to the technical field of land site selection, and provides a rural land site selection system and a control method, the rural land site selection system comprises an infrastructure layer, a data resource layer, a platform layer, an application service layer and an application system layer; the infrastructure layer is used for providing physical resources and basic software; the data resource layer is used for storing and managing related data of the rural land based on the infrastructure layer; the platform layer is used for calling related data and providing data and function support for the application service layer; the application service layer is used for providing various rural land site selection services for users based on the platform layer; and the application system layer is used for interacting with a user by using an application interface of a natural language based on the application service layer so as to realize the rural land site selection demand of the user. The system provided by the invention can improve the correlation between rural land site selection and related policies and the experience feeling of different user groups.

Methods, systems and software include programmatically downloading over the Internet, at routine intervals of time as well as on demand, from an online computer system of the USPTO, data relating to patent properties that are associated with a customer number; and creating a docket based on the downloaded data, generating and displaying a report generated from the downloaded data, sending an alert (email or text message) that is based on the downloaded data, or any combination thereof. Outgoing correspondence of the USPTO is provided in PDF format for review by a user. Data specific to a particular client also is provided to the client programmatically, with reports, alerts, docketing, or any combination thereof, further being provided for use by the client.

The invention relates to the technical field of computer-aided teaching and intelligent data processing, and discloses an English course management system applied to English teaching, which comprises a topology construction module, a prefetching buffer module, a feature analysis module, a real-time pruning module and a path presentation module. According to the system, firstly, a semantic topology network is constructed based on course metadata, and subsequent nodes and attribute data of the subsequent nodes are pre-fetched at a background according to a topological relation to construct a candidate buffer pool; meanwhile, a feature analysis module analyzes the micro-interaction behavior of the user in real time to generate a feature vector; and the real-time pruning module calculates a cognitive damping coefficient according to the cognitive damping coefficient, and dynamically filters the buffer pool by utilizing a node retention formula in combination with difficulty increment and context switching cost value. And when a submission instruction is triggered, the system locks the optimal node in time to display the adaptive content, and corrects the topological weight by using the damping coefficient. According to the method, data retrieval and cognitive state calculation are parallelized, so that course real-time adaptation and low-delay interaction based on implicit feedback are realized.

The application discloses a long-text-oriented episodic screenplay generation method and system, and belongs to the technical field of artificial intelligence content generation and digital video production. The method forms multiple episode objects through voice-over role initialization, text semantic compression and episode segmentation, and extracts role candidate objects and location time sequence candidate objects; based on normalization rules, an identity register of roles and a location time sequence register are constructed respectively, and unified identification reuse or new registration is performed on the candidate objects; under the constraint of the register, scene planning results and structured screenplay constraint patterns are generated, and multiple generation agents are called to output screenplay objects; and then, through structure verification, field completion and unified field transformation, the standardized results of episodes, roles, locations and screenplays are output. The application can improve the consistency of cross-episode roles and locations, the stability of the screenplay structure and the reuse efficiency of downstream production.