48 results about "Knowledge framework" patented technology

The Visual OOKS technology of the present invention comprising an Access Interface, which presents the user's needs and environment in terms of specified goals, outcomes and other related information, a plurality of user interfaces in which learning structures are embedded as navigational and organizational elements, and which are selected and presented to the user on the basis of the users specification of outcome or task goals, and further comprising of a retrieval engine and a tagged database such that the retrieval engine is able to select the appropriate knowledge object from the tagged database, logically organize them, and present to the user in terms of learning structure which has been prior presented to the user. The Visual OOKS platform may have an additional layer for appropriate visual presentation of the document. The Visual OOKS platform uses a unique Universal Classification Knowledge Framework (UCKF).

A distributed architecture for an enterprise portal involves a network of connected, department-sized portal servers working together as a group of federated portals, including a union of independent entities working together to provide specific functions. An enterprise portal architecture includes a number of user systems connected, over a network, to at least two portals, a plurality of data sources coupled over a network to the portals, where each of the portals include a knowledge framework unit. The knowledge framework units, which are interconnected, each include a digital business identity and a knowledge broker, wherein the digital business identity includes a user directory configured to store information unique to a subset of said plurality of users, and wherein the knowledge broker includes a meta-data directory.

A method for configuring an automated in-circuit test debugger is presented. The novel test debug and optimization configuration technique configures expert knowledge into a knowledge framework for use by an automated test debug and optimization system for automating the formulation of a valid stable in-circuit test for execution on an integrated circuit tester. In a system that includes a rule-based controller for controlling interaction between the test-head controller of an integrated circuit tester and an automated debug system, the invention includes a knowledge framework and a rule-based editor. The knowledge framework stores test knowledge in the representation of rules that represent a debugging strategy. The rule-based editor facilitates the use of rules as knowledge to debug or optimize an in-circuit test that is to be executed on the integrated circuit tester.

A method and apparatus for automatically debugging and optimizing an in-circuit test that is used to test a device under test on an automated tester is presented. The novel test debug and optimization technique extracts expert knowledge contained in a knowledge framework and automates the formulation of a valid stable, and preferably optimized, test for execution on an integrated circuit tester.

The invention belongs to the technical field of intelligent vehicle safety, and discloses an SOEKS-based intelligent vehicle knowledge expression and vehicle state abnormity determination method. Referred information having completely different properties and dimensions is abstracted to have an SOEKS-based uniform knowledge expression form; SOEKS-based uniform knowledge are accommodated in a hierarchical structured intelligent vehicle knowledge framework; vehicle normal-driving data is collected and then is stored according to SOEKS knowledge expression and framework structure, and storage information comprises original data and a summed simple rule; and, finally, for a complex combination which cannot be described by the simple rule, a vehicle normal-state model is established by utilizing a neural network technology. An abnormity is found through a difference with an acquisition training model in a normal condition, and a single-factor abnormity can be determined rapidly through simple rule experience recorded by the SOEKS structure, so determination efficiency is high; and experiments shows that the detection ratio aiming at whether a vehicle state is normal can reach more than 90%, and determination is at a millisecond grade, so a usage requirement is met.

The invention discloses a veterinary drug residue knowledge graph construction method based on weighted LDA (Latent Dirichlet Allocation). The method comprises the following steps: firstly, constructing a veterinary drug knowledge framework, and performing deep search and downloading literature by using a web crawler in combination with the knowledge framework; and aiming at topic noise existing in the LDA topic model and a feature word bias problem, performing topic mining by using a weighted LDA method, and downloading veterinary drug related literatures again; completing named entity identification and relationship extraction by using a dictionary-based model; and finally, utilizing the Neo4j graph database to construct a veterinary drug knowledge graph. The veterinary drug residue knowledge graph can be constructed, veterinary drug residue characteristic rules and causes of damage of veterinary drug residues to human bodies can be found out, the quality safety of meat, eggs and milk is guaranteed, and therefore the body health and life safety of people are protected.

The invention discloses an automatic assembly dimension chain generation method based on a body. In order to solve the problem that information description in a product assembly model is difficult totransmit and share in a computer, the invention utilizes the advantage that the ontology can realize real semantic sharing and rule description to construct an assembly model and a corresponding judgment rule, so that an ontology reasoning knowledge framework is constructed through a JESS reasoning engine. According to the method, in combination with a semantic network rule language rule base, anassembly model information unit which faces size information and is completely expressed by assembly constraint information is constructed by utilizing an ontology, a shortest assembly size chain is automatically searched out, and a closed loop, upper deviation and lower deviation are reasoned out by utilizing a rule language. The computer can automatically generate the reasonable size chain according to the assembly body, and a method is provided for intelligent generation of the assembly size chain.

Methods for hybrid manufacturing and planning and corresponding systems and computer-readable mediums. A method includes receiving, by a data processing system, a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process. The method includes instantiating a virtual workpiece. The method includes instantiating the tools definitions against a manufacturing ontology to produce virtual tools. The method includes receiving operations for the virtual tools. The method includes searching for combinations of the operations to be performed on the virtual workpiece to make the virtual workpiece correspond to the CAD model. The method includes identifying possible manufacturing solutions according to the search. The method includes selecting a manufacturing plan from the possible manufacturing solutions.

The invention discloses an ontology-based method and an assembly size chain automatic generation method described by utilizing ontology rules. The method can be used for constructing an assembly modeland a corresponding judgment rule, so that automatic reasoning and classification are carried out on the assembly constraint relation through a JESS reasoning engine, and the influence problem of matching deviation on a size chain in the assembly process is reduced. The method has the steps of constructing an ontology reasoning knowledge framework, classifying the assembly constraint relationships in combination with a semantic network rule language rule base, and dividing the assembly constraint relationships into drifting cooperation and fixed cooperation according to whether the distance between geometrical characteristics is 0 or not; recording a search path matched with drifting, and carrying out statistic analysis on the numerical value. By using the method, the size chain with theminimum deviation influence and the shortest dimension chain can be automatically designed. According to the invention, a computer can generate a reasonable size chain according to the classificationof the assembly constraints, and the method is provided for the intelligent generation of the assembly size chain.

The invention discloses a method, a device and a system for automatically establishing a user knowledge framework and a storage medium. The method comprises the following steps: acquiring user information of a client and inquiring whether knowledge framework information of the user is stored in a user information database; if not, sending a knowledge structure questionnaire page to the client, acquiring answer information sent by the client, and acquiring preliminary knowledge characteristics of the user with a pre-arranged knowledge framework establishing model according to the answer information; generating a preliminary knowledge framework report and sending the knowledge framework report to the client; receiving the grade of the preliminary knowledge framework report sent by the client; determining the preliminary knowledge framework report to be credible and storing the report when the grade is higher than or equal to a preset grade threshold. Time cost of the user for establishing a knowledge system can be saved, the systematized knowledge framework which is more accurate and better meets requirements of the user knowledge system is established, and the efficiency of the userfor knowledge acquisition is increased.

The invention provides an intelligent teaching system based on a VR technology, and the system comprises an information obtaining module which is used for obtaining the corresponding teaching information of a teacher at a teaching end at each time, and building a corresponding teaching knowledge framework; the first capture module is used for carrying out first capture on the class attending state of the student at the VR equipment end; the second capture module is used for carrying out second capture on the interactive behavior of the teaching end and the VR equipment end; and the evaluation module is used for evaluating the acceptance degree of the students based on the teaching knowledge framework based on the first capture result and the second capture result, and determining the teaching effect of the teacher. A three-dimensional virtual environment is provided for the students through the VR technology, the learning atmosphere is improved, and the teaching effect of the teacher is improved through actual capture. According to the invention, the actual listening condition of students and the actual teaching effect of teachers are known, the learning enthusiasm of the students is enhanced through interaction, live broadcasting and rebroadcasting are combined, and the listening efficiency of the students is effectively ensured.

The invention belongs to the technical field of assembly tolerance specification design and computer-aided tolerance design (CAT), and particularly relates to an assembly tolerance specification intelligent design method based on Ontology. The method specifically comprises the following steps: (1) constructing a body of an assembly tolerance specification; (2) establishing an SWRL reasoning rule of an assembly tolerance specification; (3) extracting related tolerance information of the assembly tolerance specification; (4) constructing an assembly tolerance specification instantiation ontologymodel; and (5) combining the Jess inference machine with the SWRL rule, inferring the assembly tolerance specification, and outputting a result inference result. An ontology reasoning knowledge framework for the assembly tolerance specification domain knowledge is constructed by utilizing an ontology, and an assembly tolerance specification knowledge base is expanded according to dominant domainknowledge reasoning implicit knowledge. In combination with a semantic network rule language rule base, reasoning design parameters of assembly tolerance specifications for specific design of geometric products and using environmental conditions. The consistency knowledge description framework of the assembly tolerance specification can be provided, so that a computer can automatically select appropriate tolerance principles, tolerance types, size parameters and the like according to shape and size parameters of geometric products, and a quick and effective method is provided for intelligent design of the assembly tolerance specification.

The invention discloses a corn seed selection and precise sowing decision-making method combined with a knowledge graph, and the method comprises the following steps: a), obtaining corn variety data through a web crawler, and extracting variety feature information; b) establishing a corn seed selection knowledge framework, and constructing a knowledge graph; c) preliminarily screening varieties according to a sowing area, and then determining the varieties by utilizing a mahalanobis distance algorithm according to soil nutrients; d), obtaining sowing decision data through a GPS and a field acquisition technology; e) dividing grids by using Kriging interpolation and determining interpolation points; f) determining the grid seeding rate according to a decision formula; and g) generating a shapefile format seeding rate prescription map. The method has the beneficial effects that the method completely comprises the seed selection and sowing processes in the corn sowing decision, constructs the knowledge graph to carry out seed selection decision on the corn, generates the corn sowing quantity based on the mutual influence of the farmland environment and the variety characteristics, and comprehensively utilizes the influence of production factors on the corn sowing decision.

The invention discloses a citrus knowledge modeling and large scale ontology generation method based on an agriculture eight-word policy. The method comprises the following steps: S1, based on the agriculture eight-word policy, knowledge in the citrus planting field is classified, wherein each word is corresponding to one type, and eight types are formed; S2, as for each type, concepts contained in the type are recognized, and the relationship among the concepts is built; S3, the eight types are used to form a citrus planting knowledge framework KF with the relationship among the concepts, wherein KF=(T, S), T is a citrus planting knowledge type, and S is a semantic relational layer; S4, the citrus planting knowledge framework is converted to eight sub ontologies; and S5, the eight sub ontologies are merged to form a large scale ontology. According to the method of integrating the citrus planting field knowledge based on the agriculture eight-word policy, the difficult problems of agriculture field knowledge integration and ontology collaborative development can be solved, and a complete scheme is provided for building and managing the large scale agriculture ontology.

The invention relates to a regulation and control knowledge modeling method based on a BiLSTM technology, and the method comprises the steps: constructing a power domain ontology based on the BiLSTM technology, extracting conceptual entities in the ontology, combining the conceptual entities to obtain basic terms, and manually determining important terms in the basic terms; dividing the importantterms into three categories: department units, behavior categories and information data, and defining inheritance structures among the categories by adopting a top-down method; defining attributes andconstraints of the class, thereby creating an instance of the class; and outputting the instantiated ontology according to the input text and the created instance of the class. A professional knowledge framework can be provided for regulation and control personnel, and sharing of regulation and control professional knowledge in the electric power field is achieved.

The invention belongs to the technical field of rolling bearing clearance design and computer-aided tolerance design (CAT), and particularly relates to a rolling bearing radial clearance intelligent design method based on a body. The method specifically comprises the following steps: (1) constructing a body representation model of the radial clearance of the rolling bearing; (2) establishing an SWRL reasoning rule of the radial clearance of the rolling bearing; (3) extracting tolerance information related to the radial clearance of the rolling bearing; (4) establishing an instantiated body model of the radial clearance of the rolling bearing; and (5) combining the Jess inference machine with the SWRL rule, inferring the radial clearance of the rolling bearing, and outputting a result inference result. According to the method, the body theory is introduced into the design of the radial internal clearance of the rolling bearing, an inference knowledge framework of the radial internal clearance of the rolling bearing based on body pairs is constructed, implicit knowledge is inferred according to explicit domain knowledge, and the knowledge base of the rolling bearing is expanded. Theinvention provides a consistency knowledge description framework in the field of the radial clearance of the rolling bearing, so that a computer can automatically select a reasonable radial clearancegroup and a reasonable clearance value according to the actual working condition environment of the rolling bearing, and a feasible method is provided for intellectualization of the radial clearance of the bearing.

The invention relates to an audit plan data generation method, device and equipment based on text mining. The method comprises the following steps: acquiring professional dictionary data of the auditing field and search data of the auditing field associated with the professional dictionary data of the auditing field, and performing text mining processing on the professional dictionary data of the auditing field to generate candidate word data of the auditing field. And based on the audit candidate word data and the audit field search data, training to obtain an audit field word vector. And obtaining an audit domain ontology knowledge framework, constructing an audit knowledge graph based on the audit domain ontology knowledge framework, determining an audit direction according to the audit domain word vector and the audit knowledge graph, and generating audit plan data associated with the audit direction. By adopting the method, newly added vocabularies in search data in the auditing field can be concerned in time, missing of newly added risk points is avoided, vocabularies and associated data in various aspects of the auditing field are comprehensively considered, and the accuracy of the auditing direction and the rationality of auditing plan data are improved.

The invention discloses a mobile phone assembly process knowledge framework model construction method based on transfer learning. The method comprises the following steps: A1, collecting production data of each old mobile phone assembly process produced before; a2, calculating the topological structure similarity between the assembly technological process of each old mobile phone and the assemblytechnological process of each new mobile phone, and selecting an assembly data set Xk meeting the similarity requirement; a3, taking the process requirement parameters, collected in the step A1, of the mobile phone assembling process as input, and performing feature extraction on production data through a depth sparse auto-encoder; according to the method, a large amount of labor cost can be saved, the design period of the mobile phone can be shortened, the problem of outdated data can be solved by utilizing transfer learning characteristics, the data of the previous old style mobile phone assembling process can be well utilized, and a large amount of data is provided for model training; the accuracy of a model prediction result can be improved.

The invention belongs to the technical field of computer aided tolerance design (CAT), and particularly relates to a tolerance fit automatic selection method based on an ontology. The method specifically comprises the following steps: (1) constructing a tolerance fit automatic selection ontology; (2) establishing a tolerance fit selection SWRL inference rule; (3) extracting related tolerance information of hole-shaft matching; (4) constructing an instantiated ontology model; and (5) combining a Jess inference engine with an SWRL rule, and performing inference selection and adjustment on tolerance and cooperation. Constructing an ontology reasoning knowledge framework for tolerance fit domain knowledge by using the ontology, and reasoning implicit knowledge according to dominant domain knowledge; and in combination with a semantic network rule language rule base, reasoning the optimal tolerance and cooperation according to the specific design and constraint conditions of the geometric product. According to the method, a consistency knowledge description framework of tolerance and fit selection can be provided, so that a computer can automatically select proper tolerance fit according to geometric product tolerance information, and a quick and effective method is provided for intelligent selection of product design tolerance fit.