33 results about "Semantic integration" patented technology

The invention discloses a local and non-local multi-feature semantics-based hyperspectral image classification method. The method mainly solves the problem in the prior art that the hyperspectral image classification is low in correct rate, poor in robustness and weak in spatial uniformity. The method comprises the steps of inputting images, extracting a plurality of features out of the images, dividing a data set into a training set and a testing set, mapping various features of all samples into corresponding semantic representations by a probabilistic support vector machine, constructing a local and non-local neighbor set, constructing a noise-reducing Markov random field model, conducting the semantic integration and the noise-reducing treatment, subjecting the semantic representations to iterative optimization, obtaining the categories of all samples based on semantic representations, and completing the accurate classification of hyperspectral images. According to the technical scheme of the invention, the multi-feature fusion is conducted, and the spatial information of images is fully excavated and utilized. In the case of small samples, the advantages of high classification accuracy, good robustness and excellent spatial consistency are realized. The method can be applied to the fields of military detection, map plotting, vegetation investigation, mineral detection and the like.

The invention relates to a field device information management system based on semantics and OPC UA and belongs to the combined field of the semantic network and the industrial Internet of things. Theintegral configuration of the system comprises a sensing layer, a network layer, a semantic layer and an application layer, wherein the sensing layer comprises a bottom field device and an OPC UA server, the network layer comprises each network system accessed by the OPC UA, the semantic layer comprises an OPC UA device information acquisition end, a device information management domain knowledgeontology model, a device information semantic annotation module, a semantic reasoning and query module, an ontology database and a semantic rule file, and the application layer comprises a device running state management module, a device operator management module, a device machine account management module, a device spare part management module, a device maintenance management module and a device repair management module. The management system is advantaged in that semantic integration of the heterogeneous device information is realized, through semantic reasoning and query, the relatively rich semantic knowledge in the field can be acquired, and needs of each functional module of the system are satisfied.

The invention provides an intelligent question bank system with a real-time detection and self-adaptive evolution mechanism and a method. The intelligent question bank system comprises a question type distinguishing module, a student knowledge and capability module and a question recommendation module, wherein the question type distinguishing module is used for storing questions of different types; the student knowledge and capability module is used for detecting and evaluating the knowledge level of a student in real time; the question recommendation module is used for recommending individual questions adapting to the knowledge level of the student from the question type distinguishing module after the knowledge level of the student is acquired via the student knowledge and capability module. According to the intelligent question bank system, the current education situation of examination-oriented sea tactical issues generally existing in middle and primary schools is improved, the effectiveness of question bank test education is increased, the teaching burden of teachers and the learning burden of students are relieved, and middle and primary school subject question banks oriented to intelligent test are researched and established. Key technical problems of dynamic knowledge capability models for students in middle and primary schools, the construction of question banks under the driving action of intelligent application, selection and display of individual questions, intelligent semantic integration of the question banks based on application effects and the like are researched, and a question bank support system oriented to intelligent question application to middle and primary schools is established.

The invention discloses a system and a method for detecting access control strategy collisions in a collaborative environment. Firstly the problem of semantic isomerism of access control strategy used by each region in the collaborative environment among mutually-operated regions based on role mapping is solved, and on the basis, the problem of the access control strategy collisions in the collaborative environment is solved; therefore, the system and the method are particularly suitable for use in a collaborative environment with semantic isomerism. The technology adopts an improved strategy integration algorithm based on semantic integration and a strategy collision detection algorithm based on subgraph isomorphism as main algorithms. The main activities of the detection technology for the access control strategy collision in the collaborative environment comprise strategy pre-processing, multi-region strategy integration and strategy collision detection activity. The invention can detect the access control strategy collisions caused by mutual operation among regions by role mapping, so as to avoid the safety problems of unauthorized access and the like.

The invention provides a cross-media information analysis and retrieval method, which comprises the following steps of: performing semantic integration processing on multimode information; performing expansion according to a probability latent semantic analysis model to obtain a multilayer continuous probability latent semantic analysis model for processing a continuous feature vector; learning the multilayer-continuous probability latent semantic analysis model by adopting an asymmetric learning method, and calculating the visual feature vector distribution of an image, the visual feature vector distribution of an audio and topic probability distribution; submitting a training set and a tested media object which serves as a retrieval example by a user, and calculating intra-mode and inter-mode initial similarity values of the image and the audio in the retrieval sample; constructing a propagation model, and updating the intra-mode and inter-mode similarity values according to the propagation model; and performing secondary retrieval according to the updated similarity values.

The invention discloses a data mining method based on multi-source heterogeneous patent data semantic integration. The data mining method sequentially comprises the following steps that (1) global patent data and inter-translation dictionaries are taken as data sources, and ontology study is conducted, and a patent global ontology is constructed; (2) according to corresponding attributes, a function used for judging the individual information similarity degree in each data source is constructed; (3) according to the constructed similarity degree functions, similarity information of individuals in different data sources is calculated under the guidance of the patent global ontology; (4) data mining is conducted according to the similarity information. According to the data mining method based on multi-source heterogeneous patent data semantic integration, the extracting precision of concepts and concept relations is greatly improved, patent global ontology study is achieved, and data mining efficiency and accuracy degree are greatly improved.

The invention relates to a semantic-based data service blending method, which resolves semantic character and high efficiency of the traditional Web service use and resolves supports for the Web service structured data, by encapsulation of local application, the existing data resources released via different forms in the Internet, and semantic integration and release of the Web services. The semantic-based data service blending method effectively realizes semantic integration and releases to the local application, the structured data sources and the Web services, and thereby users can high-efficiently use the existing Web services and data resources. The invention has the advantages that the invention mainly functions in semantic integration to the local application, the structured data sources and the Web services by a system, and performs Mash-up data service assembly on the base, and finally releases the assembled semantic data services. In addition, the invention realizes seamless connection for data sharing during services assembly.

The invention belongs to the technical field of computer vision, and particularly discloses a weak supervision semantic segmentation method and an application. The method comprises that: a pre-trainedsemantic erasure type region expansion classification network used for weak supervision semantic segmentation is adopted, first-stage feature extraction and high-level semantic integration classification are sequentially carried out on a picture to be semantically segmented, and a first class response graph corresponding to the picture is obtained; an area with high responsivity in the first category response diagram is erased, and second-stage high-level semantic integration classification is performed on the erased category response diagram to obtain a second category response diagram; andthe corresponding positions of the first category response diagram and the second category response diagram are added and fused to obtain a fused category response diagram, and background threshold segmentation processing is performed on the fused category response diagram to obtain a category segmentation region diagram. The erasure type region expansion classification network structure is greatly simplified, the expansion effect is good, the region expansion exploration efficiency is greatly improved, and the weak supervision semantic segmentation effect is further enhanced.

The invention is related to the AJAX field and the data mining and integrating technology field, and discloses an asynchronous interactive data mining system based on operation flow. The data mining system comprises a client-side using GWT-EXT for construction of AJAX user interface, and a server-side being arranged on a web container and including the following modules: a distributed database module based on semantic integration, an operator parameter module, an user management module and a Rapid Miner kernel module. The invention is characterized in having no use for installing software and easy operation.

The invention provides an emotion classification method. The emotion classification method comprises the steps of obtaining a word embedding matrix corresponding to a context and a word embedding matrix corresponding to a target word; according to the word embedding matrix corresponding to the context, the word embedding matrix corresponding to the target word and the first semantic activation model, obtaining context representation with enhanced target word meaning and target word representation with enhanced context semantics; obtaining context representation after semantic selection according to the context representation of the target word semantic enhancement, the target word representation of the context semantic enhancement and the semantic selection model; according to the semantic integration model, extracting syntactic representation in a syntactic dependency tree corresponding to the target sentence; and obtaining an emotion classification result corresponding to the target word according to the context representation, the syntax representation and the second semantic activation model after semantic selection. Compared with the prior art, the semantic information related to the target word in the context is fully captured, and the relationship among the context, the target word and the syntax is comprehensively considered, so that the accuracy of sentiment classification is improved.

The invention discloses a semantic decoupling-based no-proposal time sequence language positioning method, relates to the field of cross-modal content retrieval, solves the technical problems existing in an existing no-proposal positioning mechanism, and comprises the following steps: decoupling an original video, decomposing to obtain multi-level visual feature streams, and in each visual feature stream, performing in-modal and cross-modal context modeling on the basis of a candidate proposal method, so that the advantages of the candidate proposal method are kept, a cross-semantic integration mechanism is adopted, multi-modal context features after information interaction are integrated into fine-grained features, and finally, using a proposal-free positioning mechanism to directly solve the starting position and the ending position of a target video clip. The boundary positioning mechanism of the non-proposal positioning method is utilized, and meanwhile, the intermediate features are used for assisting the content understanding of the video, so that the defects of the existing non-proposal positioning mechanism are overcome.

The invention relates to a method for reusing PCB (printed circuit board) design based on a body. A PCB demand analyzing model, a PCB reusing model based on cases, a PCB design requirement responding model based on the body and a PCB design combining model are provided in the method. The PCB design requirement responding model based on the body is the core of the invention, and semantic integration of the information of all modules of a PCB can be realized through a body model, thus the method for reusing the PCB design method is realized. The invention has the advantages of applying a body technology into the PCB design of serialized products, supporting the functions of inquiry and logic combination of PCB design requirements of users, and further realizing of the method for reusing thePCB design.

The invention discloses a data query method and device for multi-source heterogeneous data, a computer readable storage medium and equipment, and the method comprises the steps: analyzing a received structured query statement for the multi-source heterogeneous data, determining a to-be-queried sub-data source and query semanteme, generating a query statement suitable for the type of the sub-data source, querying each sub-data source to obtain corresponding sub-target information, and integrating the obtained sub-target information into target information according to query semantics, so that the query of multi-source heterogeneous data can be achieved by using one query interface, the query interface of data query is simplified, therefore, query semantic maintenance of various data source types is avoided, the method has very high applicability to multi-source heterogeneous data, and the reusability of data query codes is remarkably improved. The query efficiency is effectively improved, and computing resources and storage resources are saved.

The invention discloses a service edge calculation method and system. The method comprises the following steps: collecting and managing edge data; performing preprocessing according to the collected edge data, wherein the preprocessing comprises data cleaning, data encoding and decoding and semantic integration; monitoring an acquisition process of the edge data and managing an edge data transmission message queue; and monitoring the preprocessing process of the edge data. Structured, semi-structured and unstructured coexisting service edge data acquisition, data feature automatic marking, hybrid structure intelligent preprocessing, theme self-generation and processing process real-time monitoring can be realized, and the edge data acquisition is more accurate and reliable.

The invention belongs to the field of spatial data integration and plan combination and relates to an instance-based semantic integration and multi-plan spatial data conflict detection method. The method includes steps of implementation of instance-based multi-plan spatial data classification system integration and automatic detection of multi-plan spatial data conflict patches. The instance-based semantic integration method is provided to realize integration of different land planning classification systems, and then a spatial analysis method is applied to automatic detection of land plots in land classification conflict in multiple plans. The method is applicable to quick detection and discovery of difference patches among multi-plan data in 'multi-plan integration' and 'urban space planning', and multi-plan difference patch discovery efficiency is improved.

The invention discloses a viewpoint tracking method based on geometrical reconstruction and semantic integration. The viewpoint tracking method is characterized by comprising the steps of 1, establishing the visual characteristic set of subgraphs, 2, integrating semantic characteristics, 3, active learning algorithm, 4, optimization updating, and 5, ranking and orderly linking the subgraphs to obtain a viewpoint tracking path. The viewpoint tracking method is capable of quickly and accurately detecting various remarkable regions of images, improving the accuracy of viewpoint tracking and then improving the prediction capacity of a viewpoint transfer route.

The invention provides a multi-source heterogeneous data interaction and fusion method and system oriented to a shield scene, and relates to the technical field of data fusion. Comprising the steps that multi-source heterogeneous data sources from different systems are utilized and integrated through the Webservice technology, databases in different construction scenes are established, and a multi-source database is formed; presetting micro-service granularity, and performing data transfer on the data of the multi-source database through a plurality of micro-service components; and through a unified data interaction service gateway, unified semantic query calling is performed on the data output after transfer, and multi-source heterogeneous data interaction and fusion are completed. According to the invention, the whole system is divided into a plurality of micro-services, and the micro-services communicate with one another through a unified RestAPI interface, so that the expansibility of the system is improved, and the operation and maintenance difficulty is reduced; the core data integration micro-service realizes integration of multi-source heterogeneous data sources by utilizing Webservice and ontology technologies, and the semantic integration level and data interactivity of data are effectively improved.

This invention discloses a semantic integration insurance method in IP network, which comprises divide voice data send terminal by time length and seal voice data pack; it strictly buffer and play the voice data when the voice data pack amounts to certain number received; to substitute the loss or delay voice pack with noise data; to stop the voice play process of data receiving terminal when the number of the delay or loss packs exceeds certain threshold value; to await buffer data pack number amounts to certain delay number to start the voice play process.

The invention discloses a traceable medical record classification method, and the method comprises the steps: carrying out the semantic integration on the context information of all the characters in the medical record by using the language model, and finally suppressing the influence of meaningless characters on the classification result through a gating mechanism, so the signal-to-noise ratio of intermediate data of the classification model is improved, and then the classification accuracy of medical record texts is improved. Meanwhile, meaningful characters for the classification result can be traced back through a gating value. Finally, while high-accuracy medical record classification is achieved, the gating values of the characters are output, and tracing of the character basis of medical record classification is achieved through the gating values of the characters.

The invention belongs to the field of spatial data integration and plan combination and relates to an instance-based semantic integration and multi-plan spatial data conflict detection method. The method includes steps of implementation of instance-based multi-plan spatial data classification system integration and automatic detection of multi-plan spatial data conflict patches. The instance-based semantic integration method is provided to realize integration of different land planning classification systems, and then a spatial analysis method is applied to automatic detection of land plots in land classification conflict in multiple plans. The method is applicable to quick detection and discovery of difference patches among multi-plan data in 'multi-plan integration' and 'urban space planning', and multi-plan difference patch discovery efficiency is improved.

The invention describes a method for creating a human-readable document which, besides at least one data record, comprises at least one item of semantic information describing the data record, semantics for short. The invention uses the steps:-providing the data record and the semantics in respective digital form,-producing a human-readable representation of the document on the basis of the at least one data record and the at least one semantics item,-signing the data record and the semantics, and-integrating the signed data record and the signed semantics into the human-readable representation such that it is possible to extract the signed data record and the signed semantics from the human-readable representation and that the extracted, signed data record and the extracted, signed semantics can be taken as a basis for producing an idempotent, human-readable representation of the document.

The invention discloses a method for constructing a semantic data model for a material science field based on ontology. The method comprises the following steps of: designing the semantic data model for the material science field based on the ontology, and establishing a mapping rule between the data model and the ontology; based on the semantic data model, carrying out data semantic analysis and annotation based on the ontology aiming at structured data, semi-structured data and non-structured data, constructing a semantic visual model of field data to support the semantic integration and the efficient retrieval of massive heterogeneous data in the material science field; and based on an OWL-S (ontology web language for service) technique, describing, issuing and acquiring a relevant data service to support the higher-level service semantic synergy in the material science field. The method has the advantages that the semantic integration, the intelligent inquiry and the personalized service of the data in the material science field can be realized effectively.

The present invention provides an emotion classification method, comprising: obtaining a word embedding matrix corresponding to a context and a word embedding matrix corresponding to a target word; according to the word embedding matrix corresponding to a context, a word embedding matrix corresponding to a target word, and the first semantic activation model, obtaining The context representation of target word semantic enhancement and the target word representation of context semantic enhancement; according to the context representation of target word semantic enhancement, the target word representation of context semantic enhancement and the semantic selection model, the context representation after semantic selection is obtained; according to the semantic integration model, Extract the syntactic representation in the syntactic dependency tree corresponding to the target sentence; obtain the sentiment classification result corresponding to the target word according to the context representation, syntactic representation and the second semantic activation model after semantic selection. Compared with the prior art, the present invention fully captures the semantic information related to the target word in the context, and comprehensively considers the relationship between the context, the target word and syntax, thereby improving the accuracy of emotion classification.

The invention relates to a semantic SOA (Service-oriented Architecture) integration method based on a knowledge base and supporting complex product advanced manufacturing systems. This method takes SOA as the operating space and knowledge base as the core to provide semantic support, and proposes a semantic SOA system framework, as well as the organization and establishment of knowledge base under this framework and the implementation method of semantic SOA. With the help of the existing semantic Web idea, SOA framework and knowledge base modeling framework, the present invention aims at the characteristics and specific requirements of advanced manufacturing systems for complex products, and supports the organization and representation of domain ontology, service ontology and case ontology in the knowledge base as well as the knowledge base The six key technologies, such as service semantic release, query and invocation, are designed and explained in the implementation of Semantic SOA. In order to solve the problem of semantic heterogeneity in the integrated system, and finally achieve the purpose of improving the intelligence and automation of system integration.

The invention discloses a personalized semantic integration method and system based on data space, wherein, the personalized semantic integration method based on data space is characterized in that: constructing a resource layer, and storing metadata and content data in a database; constructing a logic layer, establishing a domain ontology in the logic layer, establishing inference rules accordingto the domain ontology, and constructing a data space model in the logic layer to correlate the domain ontology and the data space model; constructing a service layer, wherein a user manages and searches information of the domain ontology according to the inference rules or directly in the service layer; and displaying the data searched by the query through the data space model, and managing thedomain ontology and the data space model through the information management. The problem that the personalized semantic integration effect of different types of metadata and content data is poor can be solved.

The invention is related to the AJAX field and the data mining and integrating technology field, and discloses an asynchronous interactive data mining system based on operation flow. The data mining system comprises a client-side using GWT-EXT for construction of AJAX user interface, and a server-side being arranged on a web container and including the following modules: a distributed database module based on semantic integration, an operator parameter module, an user management module and a Rapid Miner kernel module. The invention is characterized in having no use for installing software and easy operation.

The invention relates to a method for reusing PCB (printed circuit board) design based on a body. A PCB demand analyzing model, a PCB reusing model based on cases, a PCB design requirement responding model based on the body and a PCB design combining model are provided in the method. The PCB design requirement responding model based on the body is the core of the invention, and semantic integration of the information of all modules of a PCB can be realized through a body model, thus the method for reusing the PCB design method is realized. The invention has the advantages of applying a body technology into the PCB design of serialized products, supporting the functions of inquiry and logic combination of PCB design requirements of users, and further realizing of the method for reusing thePCB design.