45 results about "Tree representation" patented technology

Methods, systems, apparatuses, devices, and computer program products are described. A system may obtain a set of documents associated with a knowledge base for retrieval-augmented generation (RAG). The system may generate multiple representations of the information included in the documents using multiple knowledge extraction pipelines. For example, the system may generate a set of metadata-based vector embeddings based on the documents, a set of knowledge graphs based on the documents, and a set of hierarchical tree representations based on the documents. The system may receive a user query and may retrieve contextual information from the set of vector embeddings, the set of knowledge graphs, and the set of hierarchical tree representations to augment the user query for a large language model (LLM) prompt. The system may input the prompt to the LLM, and the LLM may output a response based on the user query and the contextual information.

A method of encoding or decoding a point cloud for representing a three-dimensional location of an object, the point cloud being generated by a device comprising a plurality of beam emitters. The method comprises using information from the beam emitter such as the location and angle of each beam emitter to more efficiently represent the point cloud data.

Methods, systems, apparatuses, devices, and computer program products are described. A system may obtain a set of documents associated with a knowledge base for retrieval-augmented generation (RAG). The system may generate multiple representations of the information included in the documents using multiple knowledge extraction pipelines. For example, the system may generate a set of metadata-based vector embeddings based on the documents, a set of knowledge graphs based on the documents, and a set of hierarchical tree representations based on the documents. The system may receive a user query and may retrieve contextual information from the set of vector embeddings, the set of knowledge graphs, and the set of hierarchical tree representations to augment the user query for a large language model (LLM) prompt. The system may input the prompt to the LLM, and the LLM may output a response based on the user query and the contextual information.

Embodiments of the present disclosure relate to a method, device and computer readable storage medium for data collection. The method includes: determining, based on a flag associated with at least some nodes in a tree representation in the backup system, whether a node in the tree representation is associated with a valid backup or an invalid backup; in response to determining that the node is associated with a valid backup, keeping the node and nodes referred to by the node; and in response to determining that the node is associated with an invalid backup, deleting the node.

A graphics processing system that is operable to perform ray tracing using micromaps is disclosed. A tree representation of a micromap is generated, and when it is desired to determine whether and / or how a ray interacts with a sub-region of a primitive, the tree representation of the micromap is traversed to determine a property value for the sub-region of the primitive.

A Decorative tree representation as shelves comprises a series of rigid, open, three-dimensional shelf structures 1 based on the form of an isosceles trapezium and a three-dimensional cap 2 based on t

A method of encoding or decoding a point cloud to representing a three-dimensional location of an object, the point cloud being located within a volumetric space, the method including determining at least one closest, relative to azimuthal distance, encoded node to a current node; determining an azimuthal prediction angle for each of the at least one closest encoded node; finding an averaged azimuthal prediction angle from the determined azimuthal prediction angle for each of the at least one closest encoded node; selecting an angular azimuthal context based on the averaged azimuthal predication angle; encoding information representative of the current node based on the azimuthal context to generate the bitstream of compressed point cloud data or decoding information representative of the current node based on the azimuthal context to generate the point cloud data.

A graphics processing system that is operable to perform ray tracing using micromaps is disclosed. A tree representation of a micromap is generated, and when it is desired to determine whether and / or how a ray interacts with a sub-region of a primitive, the tree representation of the micromap is traversed to determine a property value for the sub-region of the primitive.

A graphics processing system that is operable to perform ray tracing using micromaps is disclosed. A tree representation of a micromap is generated, and when it is desired to determine whether and / or how a ray interacts with a sub-region of a primitive, the tree representation of the micromap is traversed to determine a property value for the sub-region of the primitive.

A graphics processing system that provides a micromap defining property values for sub-regions of a primitive of a scene to be rendered; and generates a first tree representation of the micromap; and applies a first barycentric rotational transform to the micromap and for the first barycentric rotational transform generates a second tree representation of the micromap; and selects one of the first or second tree representations for processing as the selected tree representation. The selected tree representation of a micromap is used when it is desired to determine whether and / or how a ray interacts with a sub-region of a primitive, the tree representation of the micromap is traversed to determine a property value for the sub-region of the primitive.

In some aspects, the techniques described herein relate to systems (130) and methods (200; 300) for determining versions of a software application that are affected by a vulnerability including: receiving an indication of a detected vulnerability in a first version of a software application by a computing device (201); in response to the indication of the detected vulnerability, generating a tree representation of the first version of the software application by the computing device (203); retrieving a plurality of versions of the software application by the computing device (301), wherein each of the plurality of version is different than the first version; for each version of the software application of the plurality of versions of the software application, generating a tree representation of the version of the software application by the computing device (303); and based on the generated trees, identifying at least one version of the plurality of versions of the software application that may include the detected vulnerability by the computing device (307).

Aspects of the present disclosure involve systems, methods, devices, and the like for generating compact tree representations applicable to machine learning. In one embodiment, a system is introduced that can retrieve a decision tree structure to generate a compact tree representation model. The compact tree representation model may come in the form of a matrix design to maintain the relationships expressed by the decision tree structure.

A project success rate intelligent prediction method and device, comprising: acquiring multi-source data, and constructing a structured knowledge base containing project success cases and their characteristics; applying the merged tree representation technology and the extended transformation to the project data in the structured knowledge base to construct a data structure, realize feature extraction and substructure search; based on the project feature set, multi-dimensional feature analysis is carried out from the time dimension and the space dimension; based on the multi-dimensional feature vector, a project-platform allocation model with group fairness is constructed; for the allocation model, a polynomial time approximation algorithm based on linear programming and network flow is designed to solve the optimal allocation scheme; according to the optimal allocation scheme and the historical project success data, the improved Reed-Solomon code technology is used for feature coding to construct a project success rate prediction model; based on the prediction model, the success rate of the project to be evaluated is evaluated and the support intensity trend is predicted. The present application improves the accuracy and efficiency of project success rate prediction.

Adaptive dual tree coding may be optimized, for example, to implement a trade-off between compression efficiency and encoder complexity. For example, adaptive dual tree / single tree representation in inter slices may be conditioned on characteristics of the slice / picture, e.g., slice type, temporal layer id, and / or temporal depth of the slice being coded / decoded. Use of block-vector guided convolutional cross-component model (BVG-CCCM) may be conditioned on disabling adaptive dual tree and / or characteristics of the slice being encoded / decoded. Use of multi-type tree (MTT) split modes early termination may be conditioned on disabling of adaptive dual tree. In examples, a device (e.g., decoder / encoder) may determine a hierarchical parameter associated with a slice. The device may determine whether to enable a dual tree mode for the slice based on the hierarchical parameter for the slice. The device may decode the slice based on the determination of whether to enable the dual tree mode for the slice.

In some aspects, the techniques described herein relate to systems (130) and methods (200; 300) for determining versions of a software application that are affected by a vulnerability including: receiving an indication of a detected vulnerability in a first version of a software application by a computing device (201); in response to the indication of the detected vulnerability, generating a tree representation of the first version of the software application by the computing device (203); retrieving a plurality of versions of the software application by the computing device (301), wherein each of the plurality of version is different than the first version; for each version of the software application of the plurality of versions of the software application, generating a tree representation of the version of the software application by the computing device (303); and based on the generated trees, identifying at least one version of the plurality of versions of the software application that may include the detected vulnerability by the computing device (307).

A method may include: retrieving a plurality of code snippets from code repositories; generating a syntax representation, a property representation for each of the code snippets; receiving a query comprising a query code snippet, natural language keywords, and / or a string pattern; performing string-based matching and parser / syntax tree matching on the query and the tree representations, syntax matching on the query and the syntax representations, and property matching on the query and the property representations, wherein each of the matchings results in a score; combining the scores of the string-based matching, the parser / syntax tree matching, the syntax matching, and / or the property matching; identifying a plurality of code snippets of interest based on the combined scores; classifying the code snippets of interest using a machine learning classifier; outputting a list of the code snippets of interest with their classifications; and training the machine learning classifier based on user feedback.

Systems and methods are provided for parsing, at a server, a design file including code for a user interface, where the code is readable by the server into a tree representation having nodes, the nodes represent design elements of the user interface and includes one or more design properties, a unique identifier, and references to child elements. The server traverses the tree representation and comparing the design elements of the tree representation to a set of factors to determine when the design elements and meet a criteria to be a subcomponent for one or more components of the code of the design file. The server adds the design elements to a list of subcomponent candidates that meet at least one of the set of factors to be a subcomponent. The server generates a tree structure for the one or more components using the list of subcomponent candidates.

The invention discloses an intelligent project success rate prediction method and device, and the method comprises the steps: obtaining multi-source data, and constructing a structured knowledge base containing project success cases and features thereof; for project data in the structured knowledge base, constructing a data structure by applying a merge tree representation technology and expanded transformation, and realizing feature extraction and substructure search; performing multi-dimensional feature analysis from a time dimension and a space dimension based on the item feature set; based on the multi-dimensional feature vector, constructing a project-platform distribution model with group fairness; for the distribution model, designing a polynomial time approximation algorithm based on linear programming and network flow, and solving an optimal distribution scheme; according to the optimal allocation scheme and historical project success data, feature coding is carried out by using an improved folding Reed-Solomon code technology, and a project success rate prediction model is constructed; and based on the prediction model, performing success rate evaluation and support strength trend prediction on the to-be-evaluated project. The accuracy and efficiency of project success rate prediction are improved.

The invention relates to a microblog forwarding prediction model based on propagation tree mapping and interest noise reduction. The microblog forwarding prediction model comprises a propagation tree learning layer, an interest noise reduction learning layer and a prediction and training layer which are connected in sequence. The propagation tree learning layer determines source microblogs according to the microblogs historically forwarded by the user; the method comprises the following steps: mapping propagation contents derived from a source microblog and a propagation relation into a propagation tree, initializing the propagation tree, and then carrying out double graph pooling to generate propagation tree representation; the interest noise reduction layer generates historical forwarding microblog set representation according to the propagation tree representation and the microblogs historically forwarded by the user; interest noise reduction learning is carried out on the historical forwarding microblogs; and the prediction and training layer generates a forwarding prediction result. According to the method, propagation tree learning is carried out according to a double graph pooling mechanism, the sufficiency and accuracy of microblog representation are enhanced, the accuracy of user interest representation is enhanced according to interest noise reduction, and the accuracy of microblog forwarding prediction is improved.

The invention belongs to the field of network space security, and discloses an industrial Internet of Things unknown protocol fuzzy test method, system, device and medium, and the method comprises the steps: obtaining an execution process log of unknown protocol data in a protocol stack based on a virtual environment; according to the execution process log, establishing a tree representation structure of each bit of the unknown protocol data; obtaining the similarity of the tree representation structures of the adjacent bits, and obtaining each field of the unknown protocol data according to the similarity of the tree representation structures of the adjacent bits; obtaining the field type of each field of the unknown protocol data through an information theory measurement method; and according to a preset variation rule of the field type, generating fuzzy test data of each field of the unknown protocol data, and according to the fuzzy test data, performing a fuzzy test of the industrial Internet of Things unknown protocol. The method does not depend on industrial Internet of Things protocol documents and expert priori knowledge, efficient fuzzy testing can be carried out on unknown Internet of Things protocols, security detection is carried out on the unknown Internet of Things protocols, and security vulnerabilities in Internet of Things equipment are found.

A method for encoding or decoding a point cloud representing a three-dimensional position of an object, wherein the point cloud is located in a volumetric space, the method comprising: determining at least one closest codec node relative to an azimuth distance to a current node; determining an azimuth prediction angle for each of the at least one closest codec node; finding an average azimuth prediction angle based on the azimuth prediction angle for each of the at least one closest determined codec node; selecting an angular azimuth context based on the average azimuth prediction angle; encoding information representing the current node based on the azimuth context to generate a bit stream of compressed point cloud data or decoding information representing the current node based on the azimuth context to generate point cloud data.

The present invention provides a Chinese character recognition method based on stroke tree representation. According to the characteristic that Chinese characters can be decomposed hierarchically, the structural information of Chinese characters is fully considered and Chinese characters are represented in the form of stroke trees. Therefore, on the basis of the prior art, the one-to-many problem of sequence representation to Chinese characters is further alleviated; and because the method of the present invention gives a higher weight to the radical structure when calculating the distance, the candidate predicted Chinese characters are closer to the label Chinese characters as a whole, thereby improving the prediction accuracy. Furthermore, because the representation of the stroke tree integrates the representation advantages of the radical level and the stroke level, the neural network model has stronger robustness for samples with occlusion and blur.

In accordance with various embodiments and aspects of the invention, systems and methods are disclosed that create a system-level address map and create a report. A system description of an electronic system (e.g., integrated circuit (IC)) is received that includes configuration parameters. A tree representation of the system is created based on the interconnect of the system. Each port of the system is assigned a tree node. To create a corresponding system-level address map, the tree representation is traversed from target(s) to initiator(s), calculating the address transformation at each node. A report of the system-level address map is created, and defects such as address duplication, missing addresses, etc. can be identified and reported to the user.

The present invention discloses a template-based concurrent defect repair system and method, including: crawling defect reports of open-source projects in an open-source defect tracking system, retrieving and screening all concurrency-related defects, and extracting corresponding patch files; converting the patch files into a special change tree representation; extracting repair templates by comparing the similarity of the change trees; using the repair templates and the files to be repaired with known defect line numbers as inputs for template matching, and after successful matching, completing the repair of concurrent defects by refactoring the source code. By converting the patch files into a special change tree representation, capturing the code change context, generating more accurate and fine-grained editing scripts, and by comparing the similarity between the change trees, the present invention can dig out accurate repair templates, make better use of the syntax information of the defective code, fully explore its relationship with the context, repair more types of concurrent defects, have stronger universality and generality, and the repair is more accurate.

Systems and methods of graphics processing in which property values for sub-regions of primitives are defined by micromaps. A property value defined for a sub-region of a primitive by a micromap is used during ray tracing to determine whether and / or how a ray interacts with the sub-region of the primitive. A tree representation of a micromap is generated, and a property value for a primitive sub-region is determined by traversing the tree representation of the micromap.

The invention discloses a JSON (JavaScript Object Notation)-based system modeling language module definition graph model tree representation method, and belongs to the technical field of computer software. The method comprises the following steps: defining a model tree structure, taking a JSON object as a root node of a model, and setting packets and blocks as top layer attributes; the method comprises the following steps: defining a Package element and a Block element; designing a structure attribute and a behavior attribute of the Block module; data structures and association mechanisms are enriched; and carrying out legality verification on the model tree by adopting JSON Schema. According to the method, a modular modeling idea and standardized model structure abstraction are introduced, a model tree system which supports structure and behavior attribute expression and has relevance and hierarchy is constructed, a semantic level verification mechanism is achieved in combination with JSON Schema, and the blank of a SysML model in the aspect of Web friendly expression and verification is filled up.

This invention discloses a code incremental injection method, apparatus, electronic device, and storage medium, relating to the field of computer software development technology. The method includes: obtaining a syntax tree representation of target code; receiving a functional incremental description, wherein the functional incremental description defines the behavioral characteristics of the function to be injected; determining the injection position in the syntax tree representation based on the behavioral characteristics; generating a structured code fragment based on the code context corresponding to the injection position and the code template associated with the functional incremental description; integrating the structured code fragment into the injection position to obtain an updated syntax tree representation; and outputting the updated target code based on the updated syntax tree representation. This invention is applicable to any software development scenario requiring automated incremental expansion of existing source code, and can solve the problem that existing technologies cannot automatically determine appropriate positions in the source code and inject adaptable code according to functional requirements while maintaining the integrity of existing handwritten code.

A graphics processing system that is operable to perform ray tracing using micromaps is disclosed. A tree representation of a micromap is generated, and when it is desired to determine whether and / or how a ray interacts with a sub-region of a primitive, the tree representation of the micromap is traversed to determine a property value for the sub-region of the primitive.

The present application relates to the field of recommendation system, and discloses a point of interest recommendation method based on tree representation trajectory and multi-granularity contrast learning, comprising: obtaining user historical check-in data set and preprocessing; dividing user check-in into day level, time period level and original check-in level node according to check-in time, and constructing multi-time granularity trajectory tree structure; constructing a recommendation model integrating global enhancement and contrast learning, training and testing the model using the data set, and obtaining the prediction result. In feature extraction, a global graph is introduced for the trajectory tree structure, and graph convolution network is used to initialize the features of leaf nodes, so as to strengthen the model's ability to capture global dependency; contrast learning strategy is introduced at each granularity node level, and the model is guided to learn semantic consistent trajectory representation through positive and negative sample constraints. The present application balances local spatio-temporal constraints and global transfer rules while mining user multi-time granularity preferences, and significantly improves the accuracy and personalization of point of interest recommendation.

System and methods for processing data queries in hybrid data mesh architectures are disclosed. A method for processing data queries in hybrid data mesh architectures may include an in-memory query engine: (1) receiving, from a requestor, a data query to retrieve data; (2) parsing the data query into a parse tree; (3) converting the parse tree into a relational tree, wherein the relational tree is a tree representation of relational operators used to execute the data query; and (4) executing a data retrieval method selected from the group consisting of tree partitioning by cost and pruning using subtree replacement using a plurality of retrieval services to retrieve data from data stores identified by the data retrieval method.