85 results about "Semantic data model" patented technology

Techniques for factoring one or more source graphs into a composite graph containing nodes representing analogous elements of the source graphs and a variability graph containing nodes representing differences in the source graphs. The composite graph is made by taking analogous input trees from the source graphs and traversing the trees from top to bottom looking for nodes in each tree at each level that are analogous to the nodes at that level in the other input trees. The sets of analogous nodes are found by first automatically correlating the nodes in the level currently being examined. Correlation may, for example, be based on similar values of a property of the nodes being correlated. Representations of the sets of correlated nodes are then displayed to a user, who indicates which sets of correlated nodes are in fact analogous. The user may also indicate that the nodes in a set of correlated nodes are not analogous or that nodes that were found by the automatic correlation not to be autonomous are in fact. The analogous nodes are allocated to a corresponding node at a corresponding level in the composite graph; the other nodes are allocated to a set of anomalous nodes. One application for the techniques is managing graphs which are models of catalogs of items.

Embodiments of the invention disclose a method for semantic matching. The method comprises: receiving a to-be-matched first statement; inputting the first statement as a word segmentation model, through the word segmentation model, outputting a first word sequence after word segmentation is performed on the first statement; converting the first word sequence to a first word vector sequence; inputting the first word vector sequence to a twinborn bidirectional long short-term memory LSTM network, and outputting a second statement matched with the first statement through the twinborn bidirectional long short-term memory LSTM network. An embodiment also provides a semantic matching server, used for improving accuracy of semantic matching.

A data dependency path calculator for a semantic search engine is provided. A body of semantically related data is modeled according to a semantic data model. A user is presented a list of data elements from which they may select desired data elements. The system automatically calculates all of the possible paths through the database that may be used to retrieve meaningful data based on the selected data elements. The available data dependency paths are returned to the user for selection. The system further provides a type of data permission that allows restricted data elements to be used as a pass-through data element for relating, connecting and retrieving non-restricted data. Thus, a user can use restricted data to create data dependency paths to retrieve meaningful data. The system further provides for defining access privileges for all levels of data structures, allowing data to be secured with an increased level of granularity than previously possible.

A computer program product embodied on a non-transitory computer readable storage medium, comprising non-transitory computer executable program code configured to perform the steps of: receiving a representation of an unlabeled event; labeling the unlabeled event according to a unitary relative event ontology; and storing the labeled event in the computer readable storage medium. The unitary relative event ontology can comprise an information description vector comprising a plurality of ontological primitives, and the plurality of ontological primitives can comprise a point description element, a reference-body description element, an observer description element, a position description element, a scene description element, and a specification description element.

Techniques for reasoning data are disclosed. The techniques may include storing data in a data store which may be a semantic data store. A plurality of reasoning modules are used to reason the data in order to detect violations of one or more business policies. The reasoning modules may include semantic reasoning modules and/or pattern-based reasoning modules. Results of reasoning the data may be displayed to one or more users.

The invention discloses a convolutional neural network-based document automatic question and answer system construction method. The method comprises the following steps of: 1, constructing a theme document library; 2, constructing a word vector model; 3, carrying out theme matching; 4, constructing a word vector matrix; 5, carrying out semantic matching on the basis of a semantic model of a convolutional neural network, wherein the semantic model of the convolutional neural network is divided into three layers, the first layer is a convolutional neural network layer, the second layer is an attention layer and the third layer is a full connection layer; and 6, an answer selection process: selecting a matched answer. According to the method, a synonym dictionary does not need to be manuallyconstructed so that plenty of manpower and time cost are saved, semantic meanings of word contexts can be purposely sampled in a model training process, and an attention mechanism is added in the network so that the contribution degrees, to semantic meanings of whole sentences, of certain representative words can be enhanced.

The invention relates to a camera and robot control system based on a semantic model and an automatic adaptation method thereof. According to the method, a semantic model server-side module and a semantic model client-side module are built in a robot controller and a camera controller respectively, and the automatic adaptation of the industrial camera and the robot control system is realized through semantic modeling of the semantic model server-side module and the analysis of the semantic model client-side module. Under the condition that the function of the camera is upgraded and changed, the robot controller does not need to stop working to carry out programming on the controller again to modify the function and the command of a camera, the working flexibility of a robot system is improved, the working time is saved, and plug-and-play is achieved.

The invention discloses a semantic model based text message extraction method and device. The method comprises the steps that to-be-extracted text messages are obtained; the to-be-extracted text messages are subjected to message extraction according to extract expressions and semantic models corresponding to the extract expressions, and target messages are obtained, wherein the extract expressionscomprise a part of speech extract expression, a time extract expression and/or a rule extract expression, the semantic model corresponding to the part of speech extract expression is a statistical semantic model, the semantic model corresponding to the time extract expression is a time semantic conceptual model, and the semantic model corresponding to the rule extract expression is a rule semantic model. Accordingly, the corresponding extract expressions and the semantic models are set according to different extract requirements, message extraction is conducted on the to-be-extracted text messages, workers do not need to compile complex regular expressions one by one, the generation difficulty is lowered, the matching flexibility is improved, and therefore the method can not only improvethe extract efficiency but also lower the workload of the workers.

The invention discloses a short text classification method based on semantic graphs, which is characterized by including the steps: A, constructing a semantic graph model for each piece of text information, and combining all semantic graph models; B, comparing similarity level among different texts according to the semantic graph models and by means of a similarity computing method; and C, according to the text similarity level, classifying the texts by the aid of a text semantic graph classifier. The short text classification method based on the semantic graphs has the advantages that semantic connotations of documents can be highlighted to a maximum degree by using the graph models to represent the texts, latent semantic information and theme features in the texts can be accurately described to a great extent by the aid of the TSG (text semantic graph) models constructed by the method, and the TSG classification method can be more reliable and efficient in use as compared with other classification methods by means of the feature, so that human cost is greatly reduced, artificial arrangement of the text information is avoided to a great extent, and the text information is automatically organized by a computer.

A computer implemented method and system for insurance enterprise management and data acquisition and communication has an enterprise service bus and semantic model for communicating across different insurance businesses to retrieve data common to one service. The system and method utilizes a semantic model under a service oriented architecture which facilitates an insurance administration suite that supports user configuration of modules for use across a plurality of insurance business functions and lines. The integrated insurance administration suite supports insurance workflow management by allowing a user to configure modules to meet the needs of an insurance carrier. Insurance administration suite modules have functionality for policy, claims, billing, collections, financials, distribution, business intelligence, and reinsurance. Modules may be implemented as an integrated, enterprise solution for all lines of business that a carrier handles. The configuration features and functionality allows the entire suite to be adapted to meet the needs of the enterprise.

Campaign creation systems and methods for building semantic model based targeted search advertising campaigns in accordance with embodiments of the invention are disclosed. In one embodiment of the invention, a method of automatically generating adgroups includes obtaining source data describing a plurality of landing pages, obtaining a list of initial keywords, building a semantic model based on the source data and the initial list of keywords, mapping keywords to relevant offers based on the semantic model, automatically generating one or more anticipated creatives, automatically generating at least one anticipated creative based upon the attributes of at least one relevant offer, automatically generating adgroups using at least one of the one or more anticipated creatives, including at least one anticipated creative based upon the attributes of at least one relevant offer in the adgroup associated with the relevant offer, and deploying the adgroups to a search engine provider.

The invention discloses a remote-sensing artificial ground object identifying method based on a semantic tree model of an object. The remote-sensing artificial ground object identifying method comprises the steps of: establishing a remote-sensing ground object representative image set; splitting images in the remote-sensing ground object representative image set by adopting a multi-scale method, and obtaining an object tree of each image; modeling for each node of each object tree by adopting an LDA (linear discriminant analysis) method, and computing implied semantic features contained in the tree node objects; obtaining the object tree sets of all the images in the representative set to learn each pair of object trees in a matching way, and extracting the common maximum sub-trees from the object trees; combining all the common maximum sub-trees together by adopting a step-by-step adding method, and forming an object semantic tree of the category of the described ground object; and identifying the artificial ground object according to the object semantic tree and obtaining the area in which the ground object is positioned. The remote-sensing artificial ground object identifying method disclosed by the invention can be used for mostly effectively processing the artificial ground objects in the condition of high-resolution remote-sensing images; the identification result is accurate, the robustness is good, the applicability is high, and manual work is reduced.

The invention belongs to the field of the processing of a natural language, and particularly relates to a user search string organization name recognition method based on a semantic feature model. The method comprises a treatment process of a model establishment stage and a recognition stage. The method comprises the steps of establishing a training language database conforming to the distribution of user search strings by utilizing the existing a long text marking language database at the model establishing stage, wherein the semantic database is used for storing the features of traditional participle and part-of-speech tagging and is additionally provided with a context feature in the search string and a cohesive feature correlated semantic environment feature, establishing a condition random field model according to the composite semantic feature, and adopting the random condition field model as an organization name recognition model; calculating the semantic environment feature corresponding to the user search string to obtain a model sequence of the user inquiry string, extracting the model sequence conforming to the organization name, and obtaining an organization name in the user search string. By adopting the method, the accuracy and recall rate for recognizing the organization name in the user search string can be comprehensively improved.

A virtual storage network may be implemented and exposed as a single virtual namespace, using physical disk storage distributed across multiple computing devices. In various embodiments, each computing device contributing physical disk storage to the virtual storage network may include one or more virtual block devices configured to provide a local interface to the virtual storage network, an application programming interface (API) or other software components to translate the local data access requests into tuple-space operations compatible with the tuple-space data model, and/or a tuple-space storage engine configured to provide access to the data tuple-space of the distributed virtual storage network. The tuple-space storage engine executing on each of the computing devices of the virtual storage network may coordinate via low-level communication to satisfy data access requests from client devices, and to perform data replication and migration tasks so that devices may be seamlessly added or removed from the virtual storage network.

The invention relates to a product unified model construction system based on a semantic meta model and a construction method thereof, and belongs to the technical field of product modeling. The system comprises a human-computer interaction interface (000), a product modeling subsystem (100), a product semantic meta model definition and management subsystem (200) and a product model management subsystem (300). The human-computer interaction interface is connected with the product modeling subsystem, the product semantic meta model definition and management subsystem and the product model management subsystem. The product modeling subsystem is connected with the product semantic meta model definition and management subsystem and the product model management subsystem. Compared with the systems and the methods in the prior art, a multi-level product modeling framework is constructed through combination of the meta modeling mechanism and the ontology technology so that product geometric and non-geometric information semantic description can be realized, and product life cycle information integration, sharing and reusing can be realized; and design personnel can create normal product information models without being proficient in the ontology thought or the modeling language internal structure so that the design efficiency and quality can be enhanced.

The invention discloses a universal network protocol analysis method. The method aims at the specifications and characteristics of application layer protocols under different digital network channels, and the method comprises the following steps: 1) defining a semantic meta model for describing the application layer protocols; 2) defining modeling standards and specifications of a network application protocol; 3) describing a digital network application layer protocol model of a combat system based on a "tree" structure; and 4) designing an automatic protocol analysis method based on the semantic meta model. Verification shows that the method disclosed by the invention can satisfy the mainstream application layer protocols, and can provide guidance for the development of universal joint debugging apparatuses, test devices and simulators by means of protocol analysis requirements.

The invention discloses an image description generation method based on an architectural short sentence constraint vector and a dual visual attention mechanism, A semantic model for automatically describing the visual content information of images is obtained by training a large number of labeled texts. The semantic model is composed of three parts: a short sentence generation model, a dual visualattention mechanism and a constrained language model. The text description can be generated automatically for any input test image. The invention can effectively establish the relationship between the word and the image in the text description, and has good performance for describing the salient objects or scenes of the image based on semantics.

A computer program product embodied on a non-transitory computer readable storage medium, comprising non-transitory computer executable program code configured to perform the steps of: receiving a representation of an unlabeled event; labeling the unlabeled event according to a unitary relative event ontology; and storing the labeled event in the computer readable storage medium. The unitary relative event ontology can comprise an information description vector comprising a plurality of ontological primitives, and the plurality of ontological primitives can comprise a point description element, a reference-body description element, an observer description element, a position description element, a scene description element, and a specification description element.

The invention discloses a value added service control method and system supporting various access modes, establishing a service data model which includes at least abstractions of service and access channels, separating the access channels of the service from attribute of the service, correlating each service with corresponding access channel data table which includes one or one more access channels capable of issuing content of the service. The invention introduces a comprehensive service data model and separates access channel from attribute of the service, thereby enabling users to access service through various modes, which realizes service operations like subscribing, refunding and ordering, and effectively enriches service forms, promotes service availability and improves satisfaction of users.

The invention provides a seismic data processing method based on the alternating direction method and the total variation theory. The method comprises the steps of building a seismic data model based on total variation, using the classic quadratic penalty function method to convert the model into a solving problem meeting the requirement of iteration and alternating minimization, and performing iteration through the alternating direction method to get seismic data after recovery. By using the technology, seismic data can be de-noised and de-blurred (de-convoluted), the signal-to-noise ratio and resolution of seismic data can be improved effectively, and a good processing effect can be achieved even if the signal is seriously polluted by noise.

The invention relates to an integrated three-dimensional data modeling method for a comprehensive pipe network geographic information system, which comprises the following steps: (1) abstracting urbancomprehensive pipe network elements; (2) constructing change events of an urban comprehensive pipe network; (3) constructing an urban comprehensive pipe network element topologic relation; (4) constructing a semantic relation model for the urban comprehensive pipe network elements according to the essential characteristics and rules of the urban comprehensive pipe network; and (5) constructing aphysical data model for the urban comprehensive pipe network, and realizing the association between a geometric data model and attribute data and relation according to the physical organization of urban comprehensive pipe network data. The three-dimensional data modeling method achieves the uniformity on a model system of the urban comprehensive pipe network data, meets the requirement on expression of dynamic information of the urban comprehensive pipe network, and is worth popularizing and applying.

The invention discloses a simulator system based on a simulation data model. The simulator system comprises a configuration unit, a simulation data model unit, a task execution logical unit, a data interface unit and an auxiliary unit. The invention further discloses a method for implementing the system. The method comprises the steps of creating an interface document, creating a simulation data model memory object, creating and connecting a data source, creating tasks and operating execution logic, crating and operating the auxiliary unit, receiving an external instruction and sending simulation data and the like. Through the interface document and the execution logic, the requirements of various simulation service logics can be met; and through the data interface unit, multi-type data interfaces (including a hardware driving interface and interfaces of other forms) can be matched. The standardization and universalization degree of a simulator are greatly improved, risks caused by service alterations are reduced, and users' investments are protected.

The invention discloses a method for directly driving human animation by human motion capture data. The method is based on a semantic model, and relates to the technical fields of computer animation and human motion capture. The method comprises the following steps: the concept and the method of a human topological structure semantic model are introduced; the semantic model is taken as a connection; and on the basis of a non-uniform rational B-spline (NURBS) surface model, the method for directly driving human animation by the human motion capture data can be realized by coordinate system interpolation. An actual test shows that a retrieval method provided by the invention is able to effectively realize the driving of third dimension human animation directly by the human motion capture data, and has the advantages of good practicability and relatively high efficiency.