22 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.

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 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.

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.

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 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.

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.

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.

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.

The present invention discloses an end-to-end forest-based implicit feedback recommendation method, comprising: step 1, assuming π is fixed, learning parameters θ used in the scoring model and tree representation; step 2, fixing the scoring model s(·,·) and the tree representation parameters, and learning the mapping π between products and leaf nodes; step 3, alternately running steps 1 and 2 to generate multiple trees and corresponding scoring models, and the generated trees form a forest; when recommending, using the scoring model corresponding to each tree to perform beam search on the tree to generate a candidate set, and the candidate sets generated on each tree form a larger candidate set; using a pre-trained discriminator to sort the candidate set, and selecting the top k products as recommended products for the user. The system provided by this method, with the help of the tree and forest index structure, can be applied to any advanced user-to-product scoring model and can efficiently provide recommendation results to users based on implicit feedback data.

This invention discloses a multi-granularity tree representation method for text data, relating to the field of text data mining technology. The method includes: acquiring text data, extracting candidate keywords from the text data, and constructing a multi-granularity tree representing the text data based on the candidate keywords, wherein the multi-granularity tree includes N elements at the i-th layer. i Keyword and N i The weights corresponding to each keyword, and the relationship between the number of keywords in each layer of the multi-granularity tree, satisfy N1≥N2≥···≥N M‑2 ≥N M‑1 ≥N M This enables a multi-granularity tree representation of text data, which can represent key information of text data at different levels, thus helping to improve the utilization value of text data.

The invention discloses a vulnerability version verification method, system and equipment based on multi-source heterogeneous information, and the method comprises the steps: obtaining vulnerability information from a plurality of heterogeneous sources, extracting core elements, and carrying out formatting processing and verification to obtain structured vulnerability entries; collecting or generating a concept verification code, and positioning and generating through a vulnerability code if the concept verification code cannot be collected; performing automatic verification on the concept verification code, and recording a function call chain and a system behavior; and migrating the successfully verified concept verification code to other versions of the software, and determining the vulnerability influence range. The method further comprises the steps of selecting the core elements according to a preset priority rule, and processing the core elements by adopting a conflict resolution rule; vulnerability code positioning comprises similarity calculation, call graph analysis, symbolic execution and large language model generation; the automatic verification is executed and monitored in an isolated environment; code migration is realized by executing path tree representation, binary code comparison and path alignment. According to the method, the influence range of the vulnerability in different software versions can be accurately verified, and the vulnerability repairing efficiency is improved.

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

To provide a method and system for presenting a search tree session of a storage tree associated with a collection of data items to a user.SOLUTION: In the method, first, a computer accessing the storage tree receives a search query. The search query includes one or more verbal or non-verbal conditions for searching the storage tree. The method also creates a search tree 19200 including one or more search tree nodes based on the search query, creates one or more grouped search tree nodes each including a search tree node, node presentation parameters corresponding to how the node is to be displayed, and search query parameters corresponding to the search query, and then creates and causes a display to output a search tree representation incorporating at least one of the grouped search tree nodes for display to the user.SELECTED DRAWING: Figure 19