2712 results about "Graph based" patented technology

A system and method for programmatically generating a graphical program in response to receiving input, e.g., user or process input. The input may specify functionality of the graphical program to be generated, and also indicate a target platform. In response to the input, a graphical program implementing the specified functionality may be programmatically generated for execution on the indicated target platform. Thus, different graphical programs, or different implementations of the graphical program, may be generated, depending on the input received. The graphical program (or implementation) may be at least partly optimized for execution on the indicated target platform. The graphical program may include a block diagram portion and a user interface portion, where the block diagram portion is specified for execution on the target platform, and the user interface portion is specified for execution on a computer system coupled to the target platform, e.g., for display of a user interface.

A method and apparatus for organizing and processing interconnected pieces of information (“nodes”) using a digital computer is disclosed. Each node has elements that may be text, images, audio, video, and other computer programs. A graph-based user interface presents the individual nodes in spatial arrangements that reflect the relationships among the nodes. User interaction indicating interest in a particular node results in an increase in the “activation” of that node. This leads to an increase in the size of the presentation of that node, as well as an increase in the size of the presentation of closely related nodes. The result is a unique user interaction paradigm that allows for intuitive traversal of complex collections of nodes.

A computer-implemented method for graphically illustrating an entity and generating a text-based report therefrom includes providing a visual base representation of an entity. The base representation includes a plurality of elements at least one of which is modifiable, where the elements are each associated with a plurality of attributes. A visual diagram of a particular entity is built based upon the base representation of the entity. In this regard, at least one visual element is added to the base representation, where the added visual elements are modifiable. Accordingly, the diagram includes the elements of the base representation and the elements added to the base representation. After determining attributes associated with the added elements, a text-based report is generated from the diagram, where the report is generated based upon the elements of the diagram and the associated attributes, and where the report is automatically generated from the diagram without user input.

A digital device and a method for parsing a query, in particular a natural language query, and retrieving results from possibly multiple data sources such as relational databases or the Semantic Web. The method includes a parsing procedure for generating a graph-based logical representation of the query using semantically structured resources, consisting of a tokenizer, a node generator, a relationship generator, and a focus identificator. The digital device realizes a modularized architecture, consisting of a parser enabling the processing of a query with possibly multiple vocabularies, a query performer retrieving data of knowledge sources independently from their database management system, and a result processor merging the results.

A system and method for storing an input data network, in the form of graph is provided. The system includes a master node and a plurality of slave nodes. The master node is operable to receive the data network in the form of a graph, the graph including a plurality of vertices connected by edges; calculate a probability of co-retrieval for each of the plurality of vertices; and assign each of the plurality of vertices to one of the plurality of compute nodes based on the calculated probability of co-retrieval. Another method and system are provided for converting a dataset into a graph based index and storing the index on disk. Respective systems and methods of querying such data networks are also provided.

Embodiments are described for a method for processing graph data by executing a Markov Clustering algorithm (MCL) to find clusters of vertices of the graph data, organizing the graph data by column by calculating a probability percentage for each column of a similarity matrix of the graph data to produce column data, generating a probability matrix of states of the column data, performing an expansion of the probability matrix by computing a power of the matrix using a Map-Reduce model executed in a processor-based computing device; and organizing the probability matrix into a set of sub-matrices to find the least amount of data needed for the Map-Reduce model given that two lines of data in the matrix are required to compute a single value for the power of the matrix. One of at least two strategies may be used to computing the power of the matrix (matrix square, M²) based on simplicity of execution or improved memory usage.

The invention discloses a graph-based judgment document case similarity calculation and retrieval method. The method includes the following main steps that 1, judgment documents are collected; 2, thereasoning parts of the judgment documents are identified; 3, the case elements of the reasoning parts are analyzed; 4, case reason atlases are generated; 5, a client receives the retrieval information; 6, the case elements are extracted or mapped; 7, the reason atlases of the case elements are matched and calculated; 8, cases similar to retrieval content are returned. Meanwhile, the invention further discloses a graph-based judgment document case similarity calculation and retrieval system. The system is characterized by including a judgment document case similarity calculation device and a similar case document retrieval device. The method and the system fully consider the professional knowledge of the judgment documents, and the generated case reason atlases show the most critical elements and internal logical relations of the cases in a compressed but intuitive mode; therefore, the method and the system provide convenience for relevant persons to intuitively look over the main points of the cases, and meanwhile enable the relevant persons to accurately retrieve the relevant cases from a document library.

The invention relates to the field of point cloud processing, and specifically discloses a three-dimensional point cloud road boundary automatic extraction method. The method comprises the steps of S1, screening seed points for the whole acquired three-dimensional point cloud data set P so as to perform super voxel classification; S2, extracting boundary points between adjacent non-coplanar super voxels by using an alpha-shape algorithm; S3, extracting road boundary points by using a graph cut based energy minimization algorithm; S4, removing outliers based on an Euclidean distance clustering algorithm; and S5, fitting the extracted road boundary points into a smooth curve. The method can directly operate on the large-scale three-dimensional point cloud, can be applied to different scenes, is high in calculation speed and good in algorithm robustness, and can extract road boundaries quickly.

The invention relates to a text data-oriented threat intelligence knowledge graph construction method. The functions of automatically extracting the key information from the text threat intelligence data and constructing the threat intelligence knowledge graph are realized. The invention provides a threat intelligence knowledge graph construction method for text data. The method comprises the following steps: defining an ontology structure in the threat intelligence field; using a threat intelligence named entity recognition model based on multiple factors and a threat intelligence entity relation extraction model based on a graph neural network to obtain threat intelligence entities and relation triples from text data, and finally storing information through a graph database to form a threat intelligence knowledge graph.

The invention discloses a depth image estimating method of a binocular stereo video, which comprises the following steps of: (1) collecting a binocular stereo video image from a binocular stereo camera; (2) performing parallax estimation based on graph cut stereo matching on the binocular stereo video image; (3) performing uniformity check on a parallax image obtained by the graph cut stereo matching, and deleting the unreliable matching by self-adapting matching to reduce the wrong matching of the depth image; (4) converting the parallax image into a depth image according to the relation of the parallax and the depth; (5) performing correction optimization on the obtained depth image by a multilateral filter; and (6) outputting the depth image to finish the depth image estimation of the binocular stereo video. The method disclosed by the invention has the advantages of effectively eliminating the errors in the depth image estimation, and finally obtaining an accurate and dense depth image so as to satisfy the demand of rebuilding image quality based on a real scene.

Malware detection methods systems, and apparatus are described. Malware may be detected by obtaining a plurality of malware binary executables and a plurality of goodware binary executables, decompiling the plurality of malware binary executables and the plurality of goodware binary executable to extract corresponding assembly code for each of the plurality of malware binary executables and the plurality of goodware binary executable, constructing call graphs for each of the plurality of malware binary executables and the plurality of goodware binary executables from the corresponding assembly code, determining similarities between the call graphs using graph kernels applied to the call graphs for each of the plurality of malware binary executables and the plurality of goodware binary executables, building a malware detection model from the determined similarities between call graphs by applying a machine learning algorithm such as a deep neural network (DNN) algorithm to the determined similarities, and identifying whether a subject executable is malware by applying the built malware detection model to the subject executable.

A system and method are provided for pessimism reduction of a timing database provided for optimization of a circuit design. Pessimism is reduced through generation of a hybrid graph-based static timing analysis (GBA) and path-based static timing analysis (PBA STA) database. PBA is selectively performed on the most critical GBA identified timing violations with the goal of reducing erroneous pessimism in operational timing characteristics passed on to the physical implementation corrective optimizer module to thereby reduce unnecessary fixing and transformations upon the circuit design to correspondingly reduce design time, temporary storage space, needed processing power for timing closure and to result in a finished operable and tangible circuit device with reduced area, power requirements, and decreased cost.

One embodiment of the present invention provides a system for detecting insider attacks in an organization. During operation, the system collects data describing user activities. The system extracts information from the data that includes user information and user communications. The system then generates a topic-specific graph based on the extracted information. The system analyzes a structure of the graph to determine if one or more rules have been violated. The system may determine that a rule associated with the graph has been violated and signal an alarm in response to detecting the rule violation.

A data infrastructure for graph-based computing that combines the natural language expressiveness of the Semantic Web and the mathematical rigor of graph theory to discover meaningful associations across multiple sources towards computer-assisted serendipitous insight discovery. The process automatically integrates massive size datasets accessed using Semantic Web standards and technologies and normalizes data in graphs. The process generates a plurality of conditional probability distributions based on type-triple meta-data and triple statistics to model saliency and automatically construct and evaluate a plurality of sub-graphs based on the plurality of conditional probabilities for contextual-saliency. The process then renders a plurality of paths (i.e. sequence of associations) that model meaningful pairwise relations between objects of the normalized integrated data. The pluralities of conditional probabilities reveal and rank previously unknown associations between entities of user-interest in the knowledge graph.

The invention discloses a multi-modal action recognition method based on a depth neural network. The method comprehensively utilizes multi-modal information such as video images, optical flow diagramsand human skeleton. The specific steps are as follows: firstly, a series of preprocessing and compression are performed on the video; Obtaining an optical flow graph based on adjacent frames of the video; The human skeleton is obtained from the video frame by using the attitude estimation algorithm, and the path integral characteristics of the skeleton sequence are calculated. The obtained optical flow graph, skeleton path integration feature and original video image are input into a depth neural network with multi-branch structure to learn the abstract spatio-temporal representation of humanmotion and correctly judge its motion category. In addition, the pooling layer based on attention mechanism is connected to the video image branch, which enhances the abstract features closely related to the final motion classification results and reduces the irrelevant interference. The invention comprehensively utilizes multimodal information, and has the advantages of strong robustness and high recognition rate.

The invention relates to the technical field of traffic information service and particularly relates to a dynamic traffic information service providing method based on the map layer overlapping. The method includes that a basic geographical information system (GIS) providing basic GIS service and a road condition information server providing a road condition information file map are matched in work, the basic GIS server receives a user request and applies for the road condition information tile map with certain proportional scale and longitude and latitude range, the road condition information tile map and a local basic CIS map are overlapped to obtain a traffic information map after feedback is obtained, and the traffic information map is fed back to a user to be displayed. The road condition information server timely acquires newest real-time road condition data, conducts road condition rendering, generates a road condition information tile map, stores the map, then receives a road condition map request, extracts a corresponding road condition information tile map from a storage catalogue, and returns the map to the basic GIS server. By means of the method, overlapping efficiency and accuracy of traffic information to common maps are improved.

A method for segmenting an image includes extracting unary potentials for pixels of the input image. These can be based for each of a set of possible labels, on information for a first channel in the image, such as in the visible range of the spectrum. Pairwise potentials are extracted for neighboring pairs of pixels of the image. These can be based on information for a second channel in the image, such as in the infrared range of the spectrum. An objective function is optimized over pixels of the input image to identify labels for the pixels. The objective function is based on a combination of ones of the extracted unary and pairwise potentials. The image is then segmented, based on the identified pixel labels. The method and system can provide an improvement in segmentation over methods which use only the visible information.

A method for organizing individual collections of images or videos captured for the same event by different cameras into a master collection, wherein each individual collection forms a media stream in chronological order. A processor for extracting image features for each image or video of the media stream of each collection; constructing a graph based on the extracted features to link the images or videos from the two media streams; finding on the graph at least a pair of images or videos, each from one of the two media streams, that corresponds to correlated captured content; aligning the remaining images or videos in response to the aligned pair so that the all images or videos from the two media streams are aligned over a common timeline; and producing a master stream in chronological order of the event over a common timeline by merging the aligned individual.

The invention relates to a GPU-based equipment fault early-warning and diagnosis method for improving weighted association rules, which belongs to the field of equipment fault diagnosis and early warning. The method comprises the following steps of: constructing a graphic processing unit (GPU)-based RARG model for realizing a quick weighted association rule algorithm; mining historical monitoring data of the equipment by utilizing a GPU-based improved weighted association rule model, and constructing an association rule pattern base; monitoring the equipment data, and extracting the eigenvalue; judging whether the eigenvalue reaches the threshold, if so, determining that the equipment is in a fault state, and otherwise, determining that the equipment is in a non-fault state; if the equipment is in a non-fault state, matching related data with the association rule pattern base, if the matching succeeds, determining that the equipment is in a defect state, namely, the equipment has a potential fault, and if the matching does not succeed, returning to the step of data monitoring. The invention develops a GPU-based RARG model for realizing the quick weighted association rule algorithm, which has an important application value.

The invention relates to a method and device based on reverse engineering for automatically generating software documents. The method and device based on the reverse engineering for automatically generating the software documents comprises scanning source programs, obtaining function comments, function detail information and a mutual call relation and a mutual inclusion relation among functions, identifying and abstracting function information of functions through a natural language, generating a global function call relation graph and a global function inclusion relation graph respectively based on the function information of the functions and the mutual call relation and mutual inclusion relation among functions, automatically generating software design description documents based on the function information of the functions, the function detail information and the global function call relation graph, generating a system function graph based on the function information of the functions and the global function inclusion relation graph, and generating software requirement specification documents automatically based on the system function graph. According to the method and device based on the reverse engineering for automatically generating the software documents, the software requirement specification documents and the software design description documents are generated automatically, the reverse engineering from codes to documents is achieved, and the method and device based on the reverse engineering for automatically generating the software documents is wide in application and strong in adaptability.

A system for autonomous management of risk transfer is provided, comprising a network-connected server configured to provide an interface for a requester to submit a request; an automated underwriting processor configured to: create a contract block by compiling the request into a computational graph-based format, link the contract block to the requester, store the contract block into memory, retrieve a plurality of available underwriting agreements from memory, and create an offer list by perform computational graph operations on the contract block to determine viable risk-transfer agreements; and presenting the offer list to the requester.

The invention provides a method for classifying sports video based on a key frame of a main scene lens. The method only adopts the main scene to perform sports classification rather than classification by frames of the whole video to represent the sports video so as to effectively reduce the calculation amount of video classification. The method comprises the following steps that: firstly, the video is automatically divided into a plurality of fragments according to the lens, key frames of all the fragments are classified into a plurality of types including long shot, medium shot and close-up after subjected to adaptive threshold cluster based on graph theory, wherein the medium shot type is used as the main scene lens of the sports video, main scene information of the sports video, namely the medium shot, can be automatically and effectively extracted without depending on any prior information in the process; multiple interferences (such as judges, close-up of spectators, broadcasting effects, advertisement and other lens) in the sports video are removed; and finally, the key frame of the main scene lens is classified by an SVM classifier. The method has high accuracy for classifying the sports video.

The present disclosure relates to a system and method for electronic design automation. Embodiments may include receiving, using at least one processor, an electronic design and determining one or more graph based analysis (“GBA”) violating nodes associated with the electronic design. Embodiments may include identifying a non-covered violating node from the GBA violating nodes and determining a worst timing path through the non-covered violating node. Embodiments may further include invoking a path-based analysis (“PBA”) on the worst timing path and determining if the worst timing path satisfies the PBA analysis.

Methods and systems of controlling an autonomous vehicle are provided. A method comprises controlling operations of the vehicle based at least in part on edge costs. An edge is a representation of a path the vehicle can traverse. Edge costs are determined by an estimation system and are based on at least one of an estimated travel time for an edge and a traverse-ability of the edge. The method further comprises sensing conditions of edges the vehicle is traversing and based on the sensed conditions, dynamically updating the edge costs.

The invention discloses a drawing-model uniformity based method for automatic check of design drawings, which includes: subjecting all resource objects described in SCD (substation configuration description) and CID (configured IDE description) files, such as intelligent devices, interfaces, virtual loops, physical loops and the like, to database modeling through an RDF (resource description framework); establishing relations, such as physical and logic relations and the like, of intelligent devices in a data model of the RDF to the former intelligent devices by means of drawing AutoCAD graphs; comparing graphic information with model information to ensure result identity in drawing output and SCD/CID model output and guarantee uniformity between the drawings in the design output result and the SCD model, and checking the visual drawings to guarantee accuracy of important output results, namely SCD and CID files.