2743 results about "Graph based" patented technology

Context sensitive drag-and-drop systems, methods and user interfaces are provided in a Graphical User Interface (GUI) computing environment. Icons representing various tasks may be interactively drag-and-dropped to an adjoining graphically-based workspace in a context-based task-drop location to simply and intuitively construct a graphically-based workflow solution. A collapsible error handling failure branch may be constructed concurrently with the main branch of the workflow process. A loopback path to a higher branch may optionally be constructed for the failure branch. The workflow solution may be applied in a document printing environment for document production, a document copying environment, or an accounting environment, for example, for clear and efficient generation of workflows.

Methods and data processing system readable media have been created to graph user clickstream data over a network or at a network site to yield meaningful and visually esthetic information. In one set of embodiments, the method can comprise (i) performing a significance test on data from a network log and generating significance results. The method can also comprise (ii) determining which of network addresses and clicktrails between network addresses meet a traffic flow criterion. The data that meet a significance criterion, traffic criterion, or both can form (iii) graphable addresses and relationships. The method can further comprise (iv) generating statistics about the graphable addresses and relationships. The method can still further comprise (v) generating a graph based on the statistics about the graphable addresses and relationships, and (vi) changing any or all of the traffic flow, significance criterion, and statistics being computed, and regenerating the graph.

Systems and methods are provided for the design, development and execution of a graphical user interface using a state machine based programming paradigm integrated with a componentized graphical user interface. The present invention generates a graphical state machine representation of the graphical user interface including states for elements of the graphical user interface and any events associated with these elements. The state diagram model provides a graphical structure for handling events associated with the graphical user interface, such as events generated by inputs provided by a user via a graphical user interface element. Furthermore, functionality for the graphical user interface, such as underlying control structure, state management, and event processing can be implemented with a high level textual programming language integrated with the graphical state machine.

Embodiments of the present invention are methods for breaking one or more trapping sets in a near codeword of a failed graph-based decoder, e.g., an LDPC decoder. The methods determine, from among all bit nodes associated with one or more unsatisfied check nodes in the near codeword, which bit nodes, i.e., the suspicious bit nodes or SBNs, are most likely to be erroneous bit nodes. The methods then perform a trial in which the values of one or more SBNs are altered and decoding is re-performed. If the trial does not converge on the decoded correct codeword (DCCW), then other trials are performed until either (i) the decoder converges on the DCCW or (ii) all permitted combinations of SBNs are exhausted. The starting state of a particular trial, and the set of SBNs available to that trial may change depending on the results of previous trials.

The invention discloses a graph-based vision SLAM (simultaneous localization and mapping) method. According to the method, the matching relation between an image and visual feature can be obtained based on the natural feature probability vector representation of the image, and the relative pose between two interframes can be calculated by utilizing the space geometry relation of images. Data association of visual odometry is obtained by utilizing the corresponding relation of continuous images, so that all constraints in an image sequence can be obtained. The camera relative pose is taken as a node in a map, the space constrained relation of image interframes is taken as an edge, so that an estimated track map based on the camera relative pose is constructed. Finally, a maximum likelihood method is employed for optimizing the map, and optimized pose estimation is obtained through a random gradient descent method. Related experiments are performed in the laboratory environment based on the provided method, also the moving track of a robot is displayed, and the validity of the algorithm is confirmed.

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.

The present invention relates to a computer-based system for identifying supply chain risks and generating supply chain graphs representing an interconnected network of entities. An industrial graph database application is configured to account for direct and indirect (transitive) supplier risk and importance, based on a weighted set of measures: criticality, replaceability, centrality and distance. A graph-based model serves as an interactive and visual supply chain risk and importance explorer. A supply network is induced from textual data by applying text mining techniques to news stories and used to populate the supply chain / graph database.

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.

This invention relates to providing a system for project planning and scheduling which supports simplified, interactive, graphics-based project planning and scheduling using new planning concepts, new scheduling concepts and new graphics-based software systems. Further, this invention permits an inexperienced user to simultaneously plan and schedule a project including establishing appropriate relationship (or dependency) links between activities, also commonly referred to as tasks, and between activities and milestones. This invention offers the simplest possible scheme of thought that can tie together activities, relationships and milestones, with or without deadlines, to yield a complete, correct network project schedule in the shortest possible time.

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.

An apparatus and program product utilize a displayed pictorial representation that depicts the actual physical configuration of a plurality of hardware components in a physical computer system to facilitate the collective management of the underlying hardware components. Typically, within such a pictorial representation, a selected status is displayed for multiple of such hardware components, thereby permitting hardware components sharing common attributes or characteristics to be identified in an efficient and intuitive manner, as well as to permit collective management operations to be performed on all selected hardware components. In addition, a pictorial representation may be dynamically generated to represent the physical configuration of a plurality of hardware components within a plurality of computers. In connection with such dynamic generation, the plurality of computers may be accessed to identify the plurality of hardware components that are resident in such computers.

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.