33 results about "Distributed knowledge" patented technology

As a solution to the problem of distributed knowledge of data object definitions, data object definitions are removed from the source code. A Meta Data Service is created and made available on a network which knows the definitions of all of the objects that are used by applications that are designed to use the Meta Data Service. When an object is created, the Meta Data Service creates and stores a meta definition for the object. Data objects are passed over a network in a “soft” format. Applications within a distributed data processing system are designed in such a manner such that, at any stage of object processing, an application does not assume to understand the definition or structure of an object, nor is an application hard-coded with the object definitions. At each stage, an application queries the Meta Data Service for the meta definition of the object before proceeding with the processing of an object. The application then receives a meta definition for the data object that allows the application to perform properly tailored processing for the data object.

The invention discloses a distributed knowledge data mining device and method used for a complex network. The distributed knowledge data mining device adopts a distributed computing platform which is composed of a control unit, a computing unit and a man-machine interaction unit, wherein the innovation key is to finish the calculated amount needed by a multifarious clustering algorithm in the data mining by different servers so as to improve the efficiency of the data mining. Aiming at different knowledge data, the degrees of relation and the weights of knowledge data also can be computed by applying different standards, so that a more credible result is obtained. A second-level clustering mode is adopted in the knowledge data mining process; the result of the first-level clustering is relatively rough, but the computing complexity is very low; and the computing complexity of the second-level clustering is relatively high, but the result is more precise. By combining the first-level clustering with the second-level clustering efficiently, the distributed knowledge data mining device improves the time complexity and clustering precision greatly in comparison with the traditional first-level clustering mode. According to the invention, as a visual and direct exhibition network structure and a dynamic evolutionary process are adopted, references are provided for the prediction in the fields of disciplinary development and hotspot research.

The illustrative embodiments provide an apparatus for controlling a vehicle. In an illustrative embodiment, a vehicle is comprised of a machine controller, a steering system, a propulsion system, a braking system, a sensor system, and a knowledge base used by the machine controller. The machine controller identifies a dynamic condition and sends commands to the steering system, the propulsion system, and the braking system to move the vehicle.

Management of a task made up of a list of activities is presented. A task includes an identification of a task creator and of a set of task activities retrieved by a computer system. A user likely to perform a portion of the set of activities is identified, wherein the portion includes one or more activities of the set of activities, and at least a portion of the set of activities is selectively delegated. The delegated portion of the set of activities is sent to the identified user. A set of responses related to the portion of the set of activities is received. Whether the task is complete is determined based on a policy for establishing that the set of responses meets a configured confidence level. Such set is reported to a task creator as responsive to determining completion of the set of responses.

System and method of event-driven synchronization of a database distributed among servers connected in a tree topology, including: transmitting, from a root server, a composition request to a first level of child servers of the root server; recursively transmitting, from each child server of a first level, a composition request to child servers at a second level, wherein the second level is lower than the first level; recursively transmitting, from each child server of the second level, a notification message to child servers at the first level, wherein the notification message comprises an identification of database fragments accessible to the child server; transmitting, from child servers at the first level, respective notification messages to the root server, wherein the root server synchronizes an availability of database fragments from the respective notification messages transmitted to the root server. Subtrees may be cut from or joined to the tree topology.

A system, apparatus and application for providing robots with the ability to intelligently respond to perceived situations are described. A knowledge database is assembled automatically, based on distributed knowledge capture. The knowledge base embodies the “common sense,” that is, the consensus, of the subjects who contribute the knowledge. Systems are provided to automatically preprocess, or “clean” the information to make it more useful. The knowledge thus refined is utilized to construct a multidimensional semantic network, or MSN. The MSN provides a compact and efficient semantic representation suitable for extraction of knowledge for inference purposes and serves as the basis for task and response selection. When the robot perceives a situation that warrants a response, an appropriate subset of the MSN is extracted into a Bayes network. The resultant network is refined, and used to derive a set of response probabilities, which the robot uses to formulate a response.

A system for managing digital assets in a distributed data processing system is provided. In one embodiment, the system includes a network of data processing systems, a plurality of local knowledge management servers connected to the network wherein each of the plurality of local knowledge management servers is connected to and maintains a local digital asset repository, a central knowledge management server, and a central registry of digital assets. Each of the plurality of local knowledge management servers sends location and identifying information concerning a digital asset to the central knowledge management server whenever a digital asset is saved to a local digital asset repository corresponding to an appropriate one of the plurality of knowledge management servers. The central knowledge management server stores the location and identifying information concerning the digital asset in the central registry of digital assets.

Disclosed is a method and system for developing a virtual sensor for determining a parameter from a set of data for performing a specific function in a distributed network. The method includes collecting the set of data from one or more sensing unit, processing the collected set of data, creating a distributed knowledge database containing the pre-processed set of data, determining the parameter based upon the processed set of data in the distributed knowledge database, performing a specific function using the parameter, wherein the virtual sensor selects at least one intelligent agent for performing the specific function in the distributed network.

The invention discloses a construction method for classification detection for a distributed small-scale medical data set, and the method comprises the steps that: a teacher network is set in a central server, student networks are set in local servers of a plurality of medical institutions, the central server can access the medical data of the plurality of medical institutions, and the local server can only access the medical data of the corresponding medical institution; the central server carries out training on the teach network according to the medical data obtained from each medical institution and a preset task demand to generate a soft label; the local server carries out training on a student network according to the medical data of each medical institution to generate a hard tag, determines a real tag corresponding to the medical data, and calculates a network loss function according to the soft tag, the hard tag and the real tag; and network loss is calculated according to the loss function, and the teacher network and the student network are optimized according to the network loss to obtain the distributed knowledge distillation network. The technical problem that in the prior art, a trained learning model is poor in performance is solved.

The invention relates to the technical field of knowledge bases, in particular to a knowledge graph-based scientific semantic comprehension method, which comprises a distributed knowledge graph module, a distributed semantic analysis module and an information display module. The distributed knowledge graph module is used for carrying out feature extraction on different graphs and establishing a unique feature extraction database of the graphs; the distributed semantic analysis module is in coupling connection with the distributed mapping knowledge domain module and is used for acquiring related characteristic data of the knowledge graph from the distributed knowledge graph module, intelligently analyze and match the obtained feature data, establishing corresponding semantics matched with the unique atlas, matching and storing the unique semantic data corresponding to the different atlas, and forming a matching database corresponding to the atlas and the semantics. Data calling and atlas semantic recognition display are facilitated. According to the method, the correlation and understanding conversion relation between the atlas and semantics is solved, and the method has good practical value and popularization significance.

The invention provides a distributed knowledge graph query method and related equipment. The query efficiency of distributed knowledge graph query can be improved. The method comprises the steps that a first device obtains a target query statement input by a user; the first device processes the target query statement to obtain a target query graph; the first device performs linear segmentation on the target query graph to obtain N query sub-trees; the first device allocates the N query sub-trees to a plurality of second devices, so that the second devices perform retrieval filtering from a database according to a target query sub-tree to obtain a target candidate result set, and obtain corresponding matched candidate result sets from the plurality of second devices corresponding to the first device according to the target candidate result set, matching the first candidate result set with the matching candidate result set to obtain a pairing result, and returning the pairing result; and the first device merges and connects the pairing results corresponding to each second device in the plurality of second devices to obtain a final result set.

Techniques for distributed data placement are provided. Query workload information corresponding to a domain is determined by a data coordinator, and the query workload information is modeled as a hypergraph, where the hypergraph includes a set of vertices and a set of hyperedges, where each vertex in the set of vertices corresponds to a concept in an ontology associated with the domain. A mapping between the concept and the plurality of data nodes is generated based on the hypergraph and further based on the predefined capabilities of each of the plurality of data nodes. A distributed knowledge base is established based on the generated mapping.

The invention relates to a learning management system based on knowledge point distribution matching, which is mainly oriented to the elementary education curriculum of primary and middle schools. According to the content of knowledge points imported by teachers and the metadata of knowledge points set up in the system, the distribution of knowledge points is formed. Teachers and students can interact with each other based on distributed knowledge points. For example, teachers can set the relationship between item types and knowledge points, and students can evaluate themselves or teachers according to the mastery of knowledge points in their daily learning. Finally, at the end of the class, according to the distribution of knowledge points, we can evaluate the degree of students' knowledge mastery of the course, and make targeted supplementary learning, which can greatly improve the learning efficiency of students.

The invention discloses a summarizing system of a distributed intellectual property database. The system comprises a terminal, a server and a database, the terminal is in network data connection withthe server. The server is in network data transmission connection with the numerical control library; wherein the terminal is in network data transmission connection with the numerical control librarythrough the server, the terminal comprises a PC, an Android mobile device and an iOS mobile device, and the network data connection mode among the terminal, the server and the numerical control library is any one of 4G, 5G or wireless WIFI network connection modes; the method and the system have the advantages that by defining the intellectual property summarizing priority in dimension, under thecondition that a plurality of intellectual property summarizing paths exist in the system, summarizing of data from bottom to top is achieved by selecting one priority path.